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Application of the 316 L stainless steel (SS) is limited by its relatively low wear resistance, insufficient strength, and poor corrosion resistance in special environments. To this end, effects of Mo particles addition on the microstructure, mechanical properties, and corrosion resistance of the laser powder bed fusion (LPBF) 316 L SS are investigated in this study. The results show that the addition of Mo particles from 0 wt.% to 10 wt.% can modify the crystal orientation and improve the strength, wear resistance, and corrosion resistance of LPBF 316 L SSs. Particularly, the LPBF 316 L SS forms a biphasic structure with a similar ratio of α-Fe to γ-Fe with 5 wt.% Mo addition. As a result, the corresponding samples possess both the excellent toughness of austenitic SSs and the high strength and corrosion resistance of ferrite SSs, which reaches a high tensile strength of about 830 MPa, together with a low friction coefficient of 0.421 μ. Since the Mo particles addition is beneficial to increase the content of Cr2O3 on the samples surface from 13.48% to 22.68%, the corrosion current density of 316 L SS decreases by two orders of magnitude from 569 nA to 6 nA, while the mechanical properties remain favorable. This study is expected to serve as a reference for the preparation of LPBF SSs with excellent integrated performance.

Two-dimensional (2D) multiferroic materials with coexisting ferroelasticity (FA) and ferroelectricity (FE) have potential applications in high-density data storage and sonar detectors. Here, based on first-principles calculations, we predict a series of stable 2D FA-FE multiferroic structures, namely γ-XOOH (X = Al, Ga, and In) monolayers. By analyzing the lattice symmetry and orientational distribution of hydroxyls, we find that XOOH monolayers possess both in-plane ferroelastic and ferroelectric polarization, as well as antiferroelectric ordering caused by the anti-parallel alignment of hydroxyls. Interestingly, the perpendicular reorientation of in-plane FE polarization accompanies 90° ferroelastic switching. Besides, they show an unusual negative transverse piezoelectric effect originated from the clamping-ion term. The multiferroic properties of the XOOH monolayers provide an excellent platform to study electroelastic effects.

Growth and immunity are opposing processes that compete for cellular resources, and proper resource allocation is crucial for plant survival. BSK1 plays a key role in the regulation of both growth and immunity by associating with BRI1 and FLS2, respectively. However, it remains unclear how two antagonistic signals co-opt BSK1 to induce signal-specific activation. Here we show that the dynamic spatial reorganization of BSK1 within the plasma membrane underlies the mechanism of signal-specific activation for growth or immunity. Resting BSK1 localizes to membrane rafts as complexes. Unlike BSK1-associated FLS2 and BRI1, flg22 or exogenous brassinosteroid (BR) treatment did not decrease BSK1 levels at the plasma membrane (PM) but rather induced BSK1 multimerization and dissociation from FLS2/BSK1 or BRI1/BSK1, respectively. Moreover, flg22-activated BSK1 translocated from membrane rafts to non-membrane-raft regions, whereas BR-activated BSK1 remained in membrane rafts. When applied together with flg22, BR suppressed various flg22-induced BSK1 activities such as BSK1 dissociation from FLS2/BSK1, BSK1 interaction with MAPKKK5, and BSK translocation together with MAPKKK5. Taken together, this study provides a unique insight into how the precise control of BSK1 spatiotemporal organization regulates the signaling specificity to balance plant growth and immunity.

In multicellular and even single-celled organisms, individual components are interconnected at multiscale levels to produce enormously complex biological networks that help these systems maintain homeostasis for development and environmental adaptation. Systems biology studies initially adopted network analysis to explore how relationships between individual components give rise to complex biological processes. Network analysis has been applied to dissect the complex connectivity of mammalian brains across different scales in time and space in The Human Brain Project. In plant science, network analysis has similarly been applied to study the connectivity of plant components at the molecular, subcellular, cellular, organic, and organism levels. Analysis of these multiscale networks contributes to our understanding of how genotype determines phenotype. In this review, we summarized the theoretical framework of plant multiscale networks and introduced studies investigating plant networks by various experimental and computational modalities. We next discussed the currently available analytic methodologies and multi-level imaging techniques used to map multiscale networks in plants. Finally, we highlighted some of the technical challenges and key questions remaining to be addressed in this emerging field.

Aquaporins such as the plasma membrane intrinsic proteins (PIPs) allow water to move through cell membranes and are vital for stomatal movement in plants. Despite their importance, the dynamic changes in aquaporins during water efflux and influx have not been directly observed in real time in vivo. Here, to determine which factors regulate these changes during the bidirectional translocation of water, we examined aquaporin dynamics during the stomatal immune response to the bacterial flagellin-derived peptide flg22. The Arabidopsis (Arabidopsis thaliana) aquaporin mutant pip2;1 showed defects in the flg22-induced stomatal response. Variable-angle total internal reflection fluorescence microscopy revealed that the movement dynamics and dwell times of AQ6]GFP-AtPIP2;1 in guard cells and subsidiary cells exhibited cell type-specific dependencies on flg22. The cytoskeleton, rather than the cell wall, was the major factor regulating AtPIP2;1 dynamics, although both the cytoskeleton and cell wall might form bounded domains that restrict the diffusion of AtPIP2;1 in guard cells and subsidiary cells. Finally, our analysis revealed the different roles of cortical actin and microtubules in regulating AtPIP2;1 dynamics in guard cells, as well as subsidiary cells, under various conditions. Our observations shed light on the heterogeneous mechanisms that regulate membrane protein dynamics in plants in response to pathogens.

New imaging methodologies with high contrast and molecular specificity allow researchers to analyze dynamic processes in plant cells at multiple scales, from single protein and RNA molecules to organelles and cells, to whole organs and tissues. These techniques produce informative images and quantitative data on molecular dynamics to address questions that cannot be answered by conventional biochemical assays. Here, we review selected microscopy techniques, focusing on their basic principles and applications in plant science, discussing the pros and cons of each technique, and introducing methods for quantitative analysis. This review thus provides guidance for plant scientists in selecting the most appropriate techniques to decipher structures and dynamic processes at different levels, from protein dynamics to morphogenesis.

Machine learning (ML) accelerates the rational design and discovery of materials, where the feature plays a critical role in the ML model training. We propose a low-cost electron probability waves (EPW) descriptor based on electronic structures, which is extracted from high-symmetry points in the Brillouin zone. In the task of distinguishing ferromagnetic or antiferromagnetic material, it achieves an accuracy (ACC) at 0.92 and an area under the receiver operating characteristic curve (AUC) at 0.83 by 10-fold cross-validation. Furthermore, EPW excels at classifying metal/semiconductors and judging the direct/indirect bandgap of semiconductors. The distribution of electron clouds is an essential criterion for the origin of ferromagnetism, and EPW acts as an emulation of the electronic structure, which is the key to the achievements. Our EPW-based ML model obtains ACC and AUC equivalent to crystal graph features-based deep learning models for tasks with physical recognitions in electronic states.

Casparian strips are diagnostically modified structure mainly appeared in the endodermis, in which the radial parts of the cell walls are characterized by the deposition of lignin and suberin in the primary cell wall. As a barrier to the apoplastic movement of solutes from the cortex to the stele, Casparian strips are essential for the exclusion of salts and pathogens, selective nutrient uptake, and many other processes. With the development of biochemical analysis techniques and genetic research methods, the research in Casparian strips was increasing and has accumulated a large number of data. In this paper, we summarize the research progress in cytological structure, development processes, chemical components of Casparian strips. We focus in particular on recent advances in physiological functions and the regulation mechanism of Casparian strips during developmental processes and the response to different environmental conditions. This review can provide significant information for further investigation on the development of Casparian strips.

Asphalt bridge deck pavement is a weak bridge structure area, and early damage usually occurs in this area under vehicle loads. Due to the complexity and diversity of vehicle loads and material structures, it is difficult to truly reflect the mechanical response of bridge deck pavement under vehicle loads. This paper studies the vehicle road interaction from a microscopic perspective. In this research, the dynamic response of asphalt bridge deck pavement under multiple loads is comparatively studied, considering the mesoscopic structure of the asphalt materials. First, the compressive properties, tensile properties and interlaminar shear properties of each layer were studied through laboratory tests. Second, the asphalt mixture bridge deck pavement model, including mesostructured, was established. Then, the subprograms of the sinusoidal vibration load, rolling load and vehicle road coupling load were realised using the discrete element method (DEM). Finally, the mesomechanical response of asphalt bridge deck pavement under those three dynamic loads was comparatively studied. The study finds that there is a large difference in the mechanical response of bridge deck pavement under multiple loads. A sinusoidal vibration load can simply be the moving load, the edge of the loading area and the bottom of the lower layer bear large tensile stress, and the shear stress at the edge of the loading area is approximately 4 times that of the middle area. The rolling load can better reflect the status of the vehicle. There is a certain difference in the shear stress response between the rolling load and the sinusoidal vibration load, and the lower layer bears compressive–tensile alternating stress. Under the vehicle road coupling load, the volatility of the dynamic response is obvious due to the road roughness. Therefore, it is of vital importance to improve the abrasion resistance of the surface layer. The results show that the comprehensive consideration of multiple loads and the mesostructure can provide a more reliable method for the dynamic design of bridge deck pavement, which is of great significance for improving the durability of the pavement.

Transition-metal dichalcogenides are rich in their structural phases, e.g., $1T\ensuremath{-}\mathrm{Ta}{\mathrm{S}}_{2}$ and $1T\ensuremath{-}\mathrm{Ta}{\mathrm{Se}}_{2}$ form charge density wave (CDW) under low temperature with interesting and exotic properties. Here, we present a systematic study of different structures in two-dimensional $\mathrm{Ta}{X}_{2}$ ($X=\mathrm{S}$, Se, Te) using density-functional theory calculations with consideration of van der Waals interaction. All the normal phases present metal characteristics with various ground state and magnetic properties. The lattice reconstruction of CDW drastically affects the electronic and structural characteristics of $1T\ensuremath{-}\mathrm{Ta}{\mathrm{S}}_{2}$ and $1T\ensuremath{-}\mathrm{Ta}{\mathrm{Se}}_{2}$, leading to a transition from metal to insulator and an emergence of magnetic moment within periodic atomic clusters called the Star of David. The evaluated Heisenberg couplings indicate the weak ferromagnetic coupling between the clusters in monolayer. Furthermore, in bilayer commensurate CDW cases, we find the intriguing phenomenon of the varying magnetic properties with different stacking orders. The magnetic moment in each layer disappears when two layers are coupled, but may sustain in certain stackings of interlayer antiferromagnetic configurations.

Concerning the magnetic anisotropy and magnetic moments of the ${M}^{3+}$ $(M=\mathrm{V}, \mathrm{Cr})$ ions in ferromagnetic $(\mathrm{FM}){M\mathrm{I}}_{3}$ monolayers, which have a honeycomb pattern of edge-sharing ${M\mathrm{I}}_{6}$ octahedra, conflicting observations have been reported in experimental and theoretical studies. We resolve these conflicts by determining the magnetic anisotropy energies for the ${M}^{3+}$ ions of ${M\mathrm{I}}_{3}$ monolayers, by analyzing their preferred spin orientations in terms of the selection rules based on the highest occupied molecular orbital--lowest unoccupied molecular orbital interactions of the ${M\mathrm{I}}_{6}$ octahedra, and by discussing whether or not the ${M}^{3+}$ ions are uniaxial. Here we show that the FM monolayer ${\mathrm{VI}}_{3}$ is uniaxial, but that of ${\mathrm{CrI}}_{3}$ is not. The magnetic anisotropy energy for the ${\mathrm{V}}^{3+}({d}^{2},S=1)$ ion of ${\mathrm{VI}}_{3}$ is greater than that for the ${\mathrm{Cr}}^{3+}$ $({d}^{3},$ $S=3/2)$ ion of ${\mathrm{CrI}}_{3}$ by more than an order of magnitude (i.e., \ensuremath{\sim}8 vs \ensuremath{\sim}0.6 meV). The ${\mathrm{V}}^{3+}$ ion exhibits uniaxial magnetism because its orbital quantum number L is not zero $(L=\phantom{\rule{0.16em}{0ex}}1)$, in contrast to the ${\mathrm{Cr}}^{3+}$ ion $(L=0)$.

In multicellular and even single-celled organisms, individual components are interconnected at multiscale levels to produce enormously complex biological networks that help these systems maintain homeostasis for development and environmental adaptation. Systems biology studies initially adopted network analysis to explore how relationships between individual components give rise to complex biological processes. Network analysis has been applied to dissect the complex connectivity of mammalian brains across different scales in time and space in The Human Brain Project. In plant science, network analysis has similarly been applied to study the connectivity of plant components at the molecular, subcellular, cellular, organic, and organism levels. Analysis of these multiscale networks contributes to our understanding of how genotype determines phenotype. In this review, we summarized the theoretical framework of plant multiscale networks and introduced studies investigating plant networks by various experimental and computational modalities. We next discussed the currently available analytic methodologies and multi-level imaging techniques used to map multiscale networks in plants. Finally, we highlighted some of the technical challenges and key questions remaining to be addressed in this emerging field.

The plasma membrane is a sophisticated, organized, and highly heterogeneous structure that compartmentalizes cellular processes. To decipher the biological processes involving membrane proteins, it is necessary to analyze their spatiotemporal dynamics. However, it is difficult to directly assess the dynamics and interactions of biomolecules in living cells using traditional biochemical methods. Single-particle tracking (SPT) methods for imaging and tracking single particles conjugated with fluorescent probes offer an ideal approach to acquire valuable and complementary information about dynamic intracellular processes. SPT can be used to quantitatively monitor the diverse motions of individual particles in living cells. SPT also provides super-spatiotemporal resolution that allows early-stage or rapid response information to be obtained for a better understanding of molecular basis of associated signal transduction processes. More importantly, SPT can be used to detect the motion paths of individual biomolecules in vivo and in situ, thus unveiling the dynamic behavior of the biomolecules that support developmental processes in living cells. In this review, we give an overview of SPT methods, from image acquisition to the detection of single particles, as well as tracking and data analysis. We also discuss recent applications of SPT methods in the field of plant biology to reveal the complex biological functions of membrane proteins.

The interaction between the receptor-like kinase (RLK) FERONIA (FER) and the secreted peptide RAPID ALKALINIZATION FACTOR1 (RALF1) is vital for development and stress responses in

The interaction between the receptor-like kinase (RLK) FERONIA (FER) and the secreted peptide Rapid Alkalinization Factor 1 (RALF1) is vital for development and stress responses in Arabidopsis. Ligand-induced membrane dynamics affect the function of several RLKs, but the effects of the RALF1-FER interaction on the dynamics of FER and the ensuing effects on its functionality are poorly understood. Here, we show that RALF1 modulated the dynamics and partitioning of FER-GFP at the plasma membrane (PM). Moreover, FER was internalized by both clathrin-mediated endocytosis (CME) and clathrin-independent endocytosis (CIE) under steady state conditions. After RALF1 treatment, FER-GFP internalization was primarily enhanced via the CME pathway, raising FER-GFP levels in the vacuole. RALF1 treatment also modulated trafficking of other PM proteins such as PIN2-GFP and BRI1-GFP, increasing their vacuolar levels by enhancing their internalization. Importantly, blocking CME attenuated RALF1-mediated root growth inhibition independently of RALF1-induced early signaling, suggesting that the RALF1 can also exert its effects via the CME pathway. These findings reveal that the RALF1-FER interaction modulates plant growth and development and this may also involve endocytosis of PM proteins.

The dual-affinity nitrate transceptor NITRATE TRANSPORTER1.1 (NRT1.1) has two modes of transport and signaling, governed by Thr-101 (T101) phosphorylation. NRT1.1 regulates lateral root (LR) development by modulating nitrate-dependent basipetal auxin export and nitrate-mediated signal transduction. Here, using the Arabidopsis (Arabidopsis thaliana) NRT1.1(T101D) phosphomimetic and NRT1.1(T101A) nonphosphorylatable mutants, we found that the phosphorylation state of NRT1.1 plays a key role in NRT1.1 function during LR development. Single-particle tracking revealed that phosphorylation affected NRT1.1 spatiotemporal dynamics. The phosphomimetic NRT1.1(T101D) form showed fast lateral mobility and membrane partitioning that facilitated auxin flux under low-nitrate conditions. By contrast, nonphosphorylatable NRT1.1(T101A) showed low lateral mobility and oligomerized at the plasma membrane (PM), where it induced endocytosis via the clathrin-mediated endocytosis and microdomain-mediated endocytosis pathways under high-nitrate conditions. These behaviors promoted LR development by suppressing NRT1.1-controlled auxin transport on the PM and stimulating Ca(2+)-ARABIDOPSIS NITRATE REGULATED1 signaling from the endosome.

Detecting protein-protein interactions (PPIs) provides fundamental information for understanding biochemical processes such as the transduction of signals from one cellular location to another; however, traditional biochemical techniques cannot provide sufficient spatio-temporal information to elucidate these molecular interactions in living cells. Over the past decade, several new techniques have enabled the identification and characterization of PPIs. In this review, we summarize three main techniques for detecting PPIs in vivo, focusing on their basic principles and applications in biological studies. We place a special emphasis on their advantages and limitations, and, in particular, we introduced some uncommon new techniques, such as single-molecule FRET (smFRET), FRET-fluorescence lifetime imaging microscopy (FRET-FLIM), cytoskeleton-based assay for protein-protein interaction (CAPPI) and single-molecule protein proximity index (smPPI), highlighting recent improvements to the established techniques. We hope that this review will provide a valuable reference to enable researchers to select the most appropriate technique for detecting PPIs.

The plant transmembrane receptor kinase FLAGELLIN SENSING 2 (FLS2) is crucial for innate immunity. Although previous studies have reported FLS2-mediated signal transduction and endocytosis via the clathrin-mediated pathway, whether additional endocytic pathways affect FLS2-mediated defense responses remains unclear. Here, we show that the

The plant transmembrane receptor kinase FLAGELLIN SENSING 2 (FLS2) is critical for innate immunity. Although previous studies have reported FLS2-mediated signal transduction and endocytosis via the clathrin-mediated pathway, whether additional endocytic pathways affect FLS2-mediated defense responses remains unclear. Here, we showed that the Arabidopsis thaliana sterol-deficient mutant steroid methyltransferase 1 displays defects in immune responses induced by the flagellin-derived peptide flg22. Variable-angle total internal reflection fluorescence microscopy (VA-TIRFM) coupled with single-particle tracking showed that the spatiotemporal dynamics of FLS2-GFP changed on the millisecond time scale and the FLS2-GFP dwell time at the plasma membrane increased in cells treated with a sterol-extracting reagent, compared with untreated counterparts. We further demonstrated that flg22-induced FLS2 clustering and endocytosis involves the sterol-associated endocytic pathway, which is distinct from the clathrin-mediated pathway. Moreover, flg22 enhanced the co-localization of FLS2-GFP with the membrane microdomain marker Flot 1-mCherry and FLS2 endocytosis via the sterol-associated pathway. This indicates that plants may respond to pathogen attacks by regulating two different endocytic pathways. Taken together, our results suggest the key role of sterol homeostasis in flg22-induced plant defense responses.

This article mainly elaborated in the field of digital signal processing in, discrete signal do N point FFT transform, the frequency spectrum diagram shaft calibration set problem, researchers usually tend to be equal to frequency axis, but this may lead to frequency before and after the inconsistent problem, this article from the Angle of the sampling frequency and the odd-even N aspects carries on the analysis, get when the N is an even number shall be on the basis of the original minus fs /2, when N is odd, should be on the basis of the original minus the [(N - 1) × f 2]/2N through such method can properly set spectrum frequency scale.

Objectives This study aimed to assess the reliability and validity of the Chinese version of the 10-item Perceived Efficacy in Patient–Physician Interaction (PEPPI-10) scale in hospitalized patients with severe knee osteoarthritis in the People’s Republic of China. Methods Between January and March 2015, the Chinese versions of PEPPI, self-efficacy for exercise scale, osteoporosis self-efficacy scale, and modified fall efficacy scale were applied to assess 110 severe knee osteoarthritis patients who were hospitalized in the second ward of the department of arthroplasty surgery of Tianjin Hospital. Results The Chinese version of the PEPPI-10 scale had a high coefficient of internal consistency (Cronbach’s α coefficient, 0.907). The score of the Chinese version of PEPPI was weakly correlated with the scores of the Chinese versions of self-efficacy for exercise scale, osteoporosis self-efficacy scale, and modified fall efficacy scale. Conclusion The Chinese version of the PEPPI-10 scale exhibits sufficient internal consistency and convergent validity in hospitalized patients with severe knee osteoarthritis in the People’s Republic of China., Video abstract