A von-Neumann-like photonic processor and its application in studying quantum signature of chaos.

Photonic quantum computation plays an important role and offers unique advantages. Two decades after the milestone work of Knill-Laflamme-Milburn, various architectures of photonic processors have been proposed, and quantum advantage over classical computers has also been demonstrated. It is now the opportune time to apply this technology to real-world applications. However, at current technology level, this aim is restricted by either programmability in bulk optics or loss in integrated optics for the existing architectures of processors, for which the resource cost is also a problem. Here we present a von-Neumann-like architecture based on temporal-mode encoding and looped structure on table, which is capable of multimode-universal programmability, resource-efficiency, phase-stability and software-scalability. In order to illustrate these merits, we execute two different programs with varying resource requirements on the same processor, to investigate quantum signature of chaos from two aspects: the signature behaviors exhibited in phase space (13 modes), and the Fermi golden rule which has not been experimentally studied in quantitative way before (26 modes). The maximal program contains an optical interferometer network with 1694 freely-adjustable phases. Considering current state-of-the-art, our architecture stands as the most promising candidate for real-world applications.

Seeds exhibit the most stable elemental composition with nitrogen addition in an Inner Mongolian grassland.

Variation in biomass elemental composition of grassland plants may have important implications for ecosystem functioning in response to global change. However, relevant studies have mostly focused on variation of nitrogen (N) and phosphorus (P) concentrations in plant leaves, while few studies have evaluated other elements and plant organs of grassland species. Here, we examined the effects of N addition on multi-element concentrations, and analyzed their patterns across different organs (leaf, stem, root and seed) of five plant species in a steppe community of the Inner Mongolian grassland. Our results showed that seeds exhibited the most stable elemental composition with N addition, and that manganese (Mn) and iron (Fe) concentrations were substantially more variable than macro-elements in response to N addition. In particular, we identified a set of significant negative relationships between elemental concentrations and their corresponding CVs (coefficients of variation) for all plant organs as a whole and for each individual organ. We further found that changes in soil pH and the availability of soil nutrients contributed mostly to variation in the biomass elemental composition of major plants in this community. These findings are important for accurately assessing the effects of N deposition on the biochemical cycling of nutrient elements in grassland ecosystems, and provide critical clues for developing effective approaches to adaptively managing grassland resources as well as mitigating the impact of global change on the dryland ecosystems in the Mongolia Plateau.

Charge-density wave mediated quasi-one-dimensional Kondo lattice in stripe-phase monolayer 1T-NbSe2.

The heavy fermion physics is dictated by subtle competing exchange interactions, posing a challenge to their understanding. One-dimensional (1D) Kondo lattice model has attracted special attention in theory, because of its exact solvability and expected unusual quantum criticality. However, such experimental material systems are extremely rare. Here, we demonstrate the realization of quasi-1D Kondo lattice behavior in a monolayer van der Waals crystal NbSe2, that is driven into a stripe phase via Se-deficient line defects. Spectroscopic imaging scanning tunneling microscopy measurements and first-principles calculations indicate that the stripe-phase NbSe2 undergoes a novel charge-density wave transition, creating a matrix of local magnetic moments. The Kondo lattice behavior is manifested as a Fano resonance at the Fermi energy that prevails the entire film with a high Kondo temperature. Importantly, coherent Kondo screening occurs only in the direction of the stripes. Upon approaching defects, the Fano resonance exhibits prominent spatial 1D oscillations along the stripe direction, reminiscent of Kondo holes in a quasi-1D Kondo lattice. Our findings provide a platform for exploring anisotropic Kondo lattice behavior in the monolayer limit.

Decentralized Neural Circuits of Multisensory Information Integration in the Brain.

The brain combines multisensory inputs together to obtain a complete and reliable description of the world. Recent experiments suggest that several interconnected multisensory brain areas are simultaneously involved to integrate multisensory information. It was unknown how these mutually connected multisensory areas achieve multisensory integration. To answer this question, using biologically plausible neural circuit models we developed a decentralized system for information integration that comprises multiple interconnected multisensory brain areas. Through studying an example of integrating visual and vestibular cues to infer heading direction, we show that such a decentralized system is well consistent with experimental observations. In particular, we demonstrate that this decentralized system can optimally integrate information by implementing sampling-based Bayesian inference. The Poisson variability of spike generation provides appropriate variability to drive sampling, and the interconnections between multisensory areas store the correlation prior between multisensory stimuli. The decentralized system predicts that optimally integrated information emerges locally from the dynamics of the communication between brain areas and sheds new light on the interpretation of the connectivity between multisensory brain areas.

Sampling-based Bayesian inference in recurrent circuits of stochastic spiking neurons.

Two facts about cortex are widely accepted: neuronal responses show large spiking variability with near Poisson statistics and cortical circuits feature abundant recurrent connections between neurons. How these spiking and circuit properties combine to support sensory representation and information processing is not well understood. We build a theoretical framework showing that these two ubiquitous features of cortex combine to produce optimal sampling-based Bayesian inference. Recurrent connections store an internal model of the external world, and Poissonian variability of spike responses drives flexible sampling from the posterior stimulus distributions obtained by combining feedforward and recurrent neuronal inputs. We illustrate how this framework for sampling-based inference can be used by cortex to represent latent multivariate stimuli organized either hierarchically or in parallel. A neural signature of such network sampling are internally generated differential correlations whose amplitude is determined by the prior stored in the circuit, which provides an experimentally testable prediction for our framework.

Novel Information-Driven Smoothing Spline Linearization Method for High-Precision Displacement Sensors Based on Information Criterions.

A noise-resistant linearization model that reveals the true nonlinearity of the sensor is essential for retrieving accurate physical displacement from the signals captured by sensing electronics. In this paper, we propose a novel information-driven smoothing spline linearization method, which innovatively integrates one new and three standard information criterions into a smoothing spline for the high-precision displacement sensors' linearization. Using theoretical analysis and Monte Carlo simulation, the proposed linearization method is demonstrated to outperform traditional polynomial and spline linearization methods for high-precision displacement sensors with a low noise to range ratio in the 10-5 level. Validation experiments were carried out on two different types of displacement sensors to benchmark the performance of the proposed method compared to the polynomial models and the the non-smoothing cubic spline. The results show that the proposed method with the new modified Akaike Information Criterion stands out compared to the other linearization methods and can improve the residual nonlinearity by over 50% compared to the standard polynomial model. After being linearized via the proposed method, the residual nonlinearities reach as low as ±0.0311% F.S. (Full Scale of Range), for the 1.5 mm range chromatic confocal displacement sensor, and ±0.0047% F.S., for the 100 mm range laser triangulation displacement sensor.

Genetic deletion or pharmacological inhibition of soluble epoxide hydrolase attenuated particulate matter 2.5 exposure mediated lung injury.

Air pollution represented by particulate matter 2.5 (PM2.5) is closely related to diseases of the respiratory system. Although the understanding of its mechanism is limited, pulmonary inflammation is closely correlated with PM2.5-mediated lung injury. Soluble epoxide hydrolase (sEH) and epoxy fatty acids play a vital role in the inflammation. Herein, we attempted to use the metabolomics of oxidized lipids for analyzing the relationship of oxylipins with lung injury in a PM2.5-mediated mouse model, and found that the cytochrome P450 oxidases/sEH mediated metabolic pathway was involved in lung injury. Furthermore, the sEH overexpression was revealed in lung injury mice. Interestingly, sEH genetic deletion or the selective sEH inhibitor TPPU increased levels of epoxyeicosatrienoic acids (EETs) in lung injury mice, and inactivated pulmonary macrophages based on the MAPK/NF-κB pathway, resulting in protection against PM2.5-mediated lung injury. Additionally, a natural sEH inhibitor luteolin from Inula japonica displayed a pulmonary protective effect towards lung injury mediated by PM2.5 as well. Our results are consistent with the sEH message and protein being both a marker and mechanism for PM2.5-induced inflammation, which suggest its potential as a pharmaceutical target for treating diseases of the respiratory system.

Bimodular continuous attractor neural networks with static and moving stimuli.

We investigated the dynamical behaviors of bimodular continuous attractor neural networks, each processing a modality of sensory input and interacting with each other. We found that when bumps coexist in both modules, the position of each bump is shifted towards the other input when the intermodular couplings are excitatory and is shifted away when inhibitory. When one intermodular coupling is excitatory while another is moderately inhibitory, temporally modulated population spikes can be generated. On further increase of the inhibitory coupling, momentary spikes will emerge. In the regime of bump coexistence, bump heights are primarily strengthened by excitatory intermodular couplings, but there is a lesser weakening effect due to a bump being displaced from the direct input. When bimodular networks serve as decoders of multisensory integration, we extend the Bayesian framework to show that excitatory and inhibitory couplings encode attractive and repulsive priors, respectively. At low disparity, the bump positions decode the posterior means in the Bayesian framework, whereas at high disparity, multiple steady states exist. In the regime of multiple steady states, the less stable state can be accessed if the input causing the more stable state arrives after a sufficiently long delay. When one input is moving, the bump in the corresponding module is pinned when the moving stimulus is weak, unpinned at intermediate stimulus strength, and tracks the input at strong stimulus strength, and the stimulus strengths for these transitions increase with the velocity of the moving stimulus. These results are important to understanding multisensory integration of static and dynamic stimuli.

The roles of stomatal morphologies in transpiration and nutrient transportation between grasses and forbs in a temperate steppe.

BACKGROUND AND AIMS: Grasses and forbs are dominant functional groups in temperate grasslands and display substantial differences in many biological traits, especially in root and stomatal morphologies, which are closely related to the use of water and nutrients. However, few studies have investigated the differences in nutrient accumulation and stomatal morphology-mediated transportation of water and nutrients from roots to shoots comparatively between the two functional groups. METHODS: Here, we explored the patterns of accumulation of multiple nutrients (N, P, K, Ca, Mg and S) in leaves and roots, transpiration-related processes and interactions between nutrients and transpiration at functional group levels by experiments in a temperate steppe and collection of data from the literature. KEY RESULTS: The concentrations of all the examined nutrients were obviously higher in both leaves and roots of forbs than those in grasses, especially for leaf Ca and Mg concentrations. Grasses with dumbbell-shaped stomata displayed significantly lower transpiration and stomatal conductance than forbs with kidney-shaped stomata. In contrast, grasses showed much higher water-use efficiency (WUE) than forbs. The contrasting patterns of nutrient accumulation, transpiration and WUE between grasses and forbs were less sensitive to varied environments. Leaf N, P and S concentrations were not affected by transpiration. In contrast, leaf Mg concentrations were positively correlated with transpiration in forb species. Furthermore, linear regression and principal component analysis showed that leaf Ca and Mg concentrations were positively correlated with transpiration between the two functional groups. CONCLUSIONS: Our results revealed contrasting differences in acquisition of multiple nutrients and transpiration between grasses and forbs, and that stomatal morphologies are an important driver for the distinct WUE and translocation of Ca and Mg from roots to leaves between the two functional groups in temperate steppes. These findings will contribute to our understanding of the important roles of functional traits in driving water and nutrient cycling.

Manipulating single excess electrons in monolayer transition metal dihalide.

Polarons are entities of excess electrons dressed with local response of lattices, whose atomic-scale characterization is essential for understanding the many body physics arising from the electron-lattice entanglement, yet difficult to achieve. Here, using scanning tunneling microscopy and spectroscopy (STM/STS), we show the visualization and manipulation of single polarons in monolayer CoCl2, that are grown on HOPG substrate via molecular beam epitaxy. Two types of polarons are identified, both inducing upward local band bending, but exhibiting distinct appearances, lattice occupations and polaronic states. First principles calculations unveil origin of polarons that are stabilized by cooperative electron-electron and electron-phonon interactions. Both types of polarons can be created, moved, erased, and moreover interconverted individually by the STM tip, as driven by tip electric field and inelastic electron tunneling effect. This finding identifies the rich category of polarons in CoCl2 and their feasibility of precise control unprecedently, which can be generalized to other transition metal halides.

Representational Geometries Reveal Differential Effects of Response Correlations on Population Codes in Neurophysiology and Functional Magnetic Resonance Imaging.

Two sensory neurons usually display trial-by-trial spike-count correlations given the repeated representations of a stimulus. The effects of such response correlations on population-level sensory coding have been the focal contention in computational neuroscience over the past few years. In the meantime, multivariate pattern analysis (MVPA) has become the leading analysis approach in functional magnetic resonance imaging (fMRI), but the effects of response correlations among voxel populations remain underexplored. Here, instead of conventional MVPA analysis, we calculate linear Fisher information of population responses in human visual cortex (five males, one female) and hypothetically remove response correlations between voxels. We found that voxelwise response correlations generally enhance stimulus information, a result standing in stark contrast to the detrimental effects of response correlations reported in empirical neurophysiological studies. By voxel-encoding modeling, we further show that these two seemingly opposite effects actually can coexist within the primate visual system. Furthermore, we use principal component analysis to decompose stimulus information in population responses onto different principal dimensions in a high-dimensional representational space. Interestingly, response correlations simultaneously reduce and enhance information on higher- and lower-variance principal dimensions, respectively. The relative strength of the two antagonistic effects within the same computational framework produces the apparent discrepancy in the effects of response correlations in neuronal and voxel populations. Our results suggest that multivariate fMRI data contain rich statistical structures that are directly related to sensory information representation, and the general computational framework to analyze neuronal and voxel population responses can be applied in many types of neural measurements.SIGNIFICANCE STATEMENT Despite the vast research interest in the effect of spike-count noise correlations on population codes in neurophysiology, it remains unclear how the response correlations between voxels influence MVPA in human imaging. We used an information-theoretic approach and showed that unlike the detrimental effects of response correlations reported in neurophysiology, voxelwise response correlations generally improve sensory coding. We conducted a series of in-depth analyses and demonstrated that neuronal and voxel response correlations can coexist within the visual system and share some common computational mechanisms. These results shed new light on how the population codes of sensory information can be evaluated via different neural measurements.

lncRNA MtCIR2 positively regulates plant-freezing tolerance by modulating CBF/DREB1 gene clusters.

Emerging evidence suggests that long noncoding RNAs (lncRNAs) are involved in regulation of plant response to environmental stress. CBF/DREB1s are highly conserved transcription factors that regulate response to cold stress in plants. However, very few lncRNAs were found to regulate expression of CBFs and cold tolerance in plant. Here, we identified a cold-responsive long intergenic noncoding RNA (MtCIR2) of CBF/DREB1 genes that were located in a major freezing tolerance QTL region of legume Medicago truncatula. We found that response of MtCIR2 transcription was more rapid than that of MtCBF/DREB1s during cold treatment. MtCIR2 positively regulated M. truncatula freezing tolerance, such that overexpression of MtCIR2 led to higher survival rate and lower cell membrane damage than wild-type plants, while mutation of MtCIR2 rendered the mutants more sensitive to cold stress. In addition, expression levels of MtCBF/DREB1s were up-regulated in the MtCIR2 overexpressing lines and down-regulated in the mutants. Among the MtCIR2-regulated genes, the strongest enriched genes were those involved in polysaccharide metabolic processes. In addition, we demonstrated that overexpression of MtCIR2 led to increases in contents of soluble sugars. These results highlight that MtCIR2 positively regulates tolerance to freezing by regulating MtCBF/DREB1s expression and glycometabolism in M. truncatula.

Morphological and physiological traits of dominant plant species in response to mowing in a temperate steppe.

Mowing is common grassland management to feed livestock during winter by harvesting hay in many high-latitude regions in autumn. The trait-based approach has been used to explain the responses of the plant community to disturbance resulting from environmental changes and human activities. However, few studies have focused on the mechanisms underlying the responses of grassland ecosystems to mowing from the perspective of plant traits. Here, we investigated the effects of mowing on the plant community of a temperate steppe in Inner Mongolia of northern China by field experiments to dissect the trade-off between morphological and physiological traits in response to short-term (4 years) and long-term (16 years) mowing. Specifically, we evaluated the two strategies associated with the nutrient acquisition of two dominant species in response to mowing by measuring leaf and root morphological traits and physiological traits of root carboxylate exudation, arbuscular mycorrhizal fungi (AMF) colonization and soil microbial community. We found that long-term mowing, but not short-term mowing, led to an increase in species richness. In addition, mowing decreased the overall plant biomass of the grassland community, but enhanced and suppressed the growth of forbs and grasses, respectively. However, the ratio of forbs to grasses in the community was dependent on mowing duration, such that forbs became more dominant than the grasses under long-term mowing. Our results revealed that short-term mowing reduced soil microbial biodiversity and root colonization of AMF in the grass Stipa krylovii, while the root AMF colonization and carboxylate exudation in the forb Artemisia frigida were enhanced by short-term mowing. In long-term mowing, the functional traits associated with leaf resource conservation (i.e., leaf tissue density) and root resource acquisition were reduced in the grass, while the functional traits related to leaf resource acquisition and root resource conservation were increased in the forb, highlighting the species specificity and divergence in leaf and root traits in the grass and forb of temperate steppe in response to mowing. These novel findings demonstrate that physiological and morphological strategies are the main drivers for dominant species in response to mowing in temperate grasslands.

Manipulating Hubbard-type Coulomb blockade effect of metallic wires embedded in an insulator.

Correlated states have emerged in low-dimensional systems owing to enhanced Coulomb interactions. Elucidating these states requires atomic-scale characterization and delicate control capabilities. Herein, spectroscopic imaging-scanning tunneling microscopy was employed to investigate the correlated states residing in 1D electrons of the monolayer and bilayer MoSe2 mirror twin boundary (MTB). The Coulomb energies, determined by the wire length, drive the MTB into two types of ground states with distinct respective out-of-phase and in-phase charge orders. The two ground states can be reversibly converted through a metastable zero-energy state with in situ voltage pulses, which tune the electron filling of the MTB via a polaronic process, substantiated by first-principles calculations. Our Hubbard model calculation with an exact diagonalization method reveals the ground states as correlated insulators from an on-site U-originated Coulomb interaction, dubbed the Hubbard-type Coulomb blockade effect. Our study lays a foundation for understanding and tailoring correlated physics in complex systems.

Mowing accelerates phosphorus cycling without depleting soil phosphorus pool.

Mowing, as a common grassland utilization strategy, affects nutrient status in soil by plant biomass removal. Phosphorus (P) cycle plays an important role in determining grassland productivity. However, few studies have addressed the impacts of mowing on P cycling in grassland ecosystems. Here, we investigated the effects of various mowing regimes on soil P fractions and P accumulation in plants and litters. We specifically explored the mechanisms by which mowing regulates ecosystem P cycling by linking aboveground community with soil properties. Our results showed that mowing increased soil dissolvable P concentrations, which probably met the demand for P absorption and utilization by plants, thus contributing to an increased P accumulation by plants. Mowing promoted grassland P cycling by a reciprocal relationship between plants and microbes. Short-term mowing enhanced P cycling mainly through increased root exudation-evoked the extracellular enzyme activity of microbes rather than the alternations in microbial biomass and community composition. Long-term mowing increased P cycling mainly by promoting carbon allocation to roots, thereby leading to greater microbial metabolic activity. Although mowing-stimulation of organic P mineralization lasted for 15 consecutive years, mowing did not result in soil P depletion. These results demonstrate that P removal by mowing will not necessarily lead to soil P limitation. Our findings would advance the knowledge on soil P dynamic under mowing and contribute to resource-efficient grassland management.

Inhibition effect of 1-acetoxy-6α-(2-methylbutyryl)eriolanolide toward soluble epoxide hydrolase: Multispectral analysis, molecular dynamics simulation, biochemical, and in vitro cell-based studies.

Soluble epoxide hydrolase (sEH) serves as a potential target in inflammation-related diseases. Based on the bioactivity-guided separation, a new sesquiterpenoid inulajaponoid A (1) was isolated from Inula japonica with a sEH inhibitory effect, together with five known compounds, such as 1-O-acetyl-6-O-isobutyrylbritannilactone (2), 6ß-hydroxytomentosin (3), 1ß,8ß-dihydroxyeudesma-4(15),11(13)-dien-12,6α-olide (4), (4S,6S,7S,8R)-1-O-acetyl-6-O-(3-methylvaleryloxy)-britannilactone (5), and 1-acetoxy-6α-(2-methylbutyryl)eriolanolide (6). Among them, compounds 1 and 6 were assigned as mixed and uncompetitive inhibitors, respectively. The result of immunoprecipitation (IP)-MS demonstrated the specific binding of compound 6 to sEH in the complex system, which was further confirmed by the fluorescence-based binding assay showing its equilibrium dissociation constant (Kd = 2.43 µM). The detail molecular stimulation revealed the mechanism of action of compound 6 with sEH through the hydrogen bond of amino acid residue Gln384. Furthermore, this natural sEH inhibitor (6) could suppress the MAPK/NF-κB activation to regulate inflammatory mediators, such as NO, TNF-α, and IL-6, which confirmed the anti-inflammatory effect of inhibition of sEH by 6. These findings provided a useful insight to develop sEH inhibitors upon the sesquiterpenoids.

MicroRNA­124: an emerging therapeutic target in central nervous system disorders.

The central nervous system (CNS) consists of neuron and non-neuron cells including neural stem/precursor cells (NSPCs), neuroblasts, glia cells (mainly astrocyte, oligodendroglia and microglia), which thereby form a precise and complicated network and exert diverse functions through interactions of numerous bioactive ingredients. MicroRNAs (miRNAs), with small size approximately ~ 21nt and as well-documented post-transcriptional key regulators of gene expression, are a cluster of evolutionarily conserved endogenous non-coding RNAs. More than 2000 different miRNAs has been discovered till now. MicroRNA-124(miR-124), the most brain-rich microRNA, has been validated to possess important functions in the central nervous system, including neural stem cell proliferation and differentiation, cell fate determination, neuron migration, synapse plasticity and cognition, cell apoptosis etc. According to recent studies, herein, we provide a review of this conversant miR-124 to further understand the potential functions and therapeutic and clinical value in brain diseases.

Intraoperative Low-Dose S-Ketamine Reduces Depressive Symptoms in Patients with Crohn's Disease Undergoing Bowel Resection: A Randomized Controlled Trial.

Background: Patients with Crohn's disease (CD) undergoing bowel resection often suffer from depression and acute pain, which severely impairs their recovery. We aimed to investigate the effects of S-ketamine preconditioning on postoperative depression in patients with CD undergoing a bowel resection with mild to moderate depression and to observe whether it can relieve postoperative pain and anti-inflammation. Methods: A total of 124 adult patients were randomized into one of the two groups. Patients in the S-ketamine group received a 0.25 mg/kg S-ketamine intravenous drip under general anesthesia induction, followed by a continuous infusion of S-ketamine with 0.12 mg/kg/h for more than 30 min through target-controlled infusion. Patients in the placebo group received 0.9% saline at an identical volume and rate. The primary outcome measure was the 17-item Hamilton depression Scale (HAMD-17). The secondary outcomes were scores on the following questionnaires: a nine-item patient health questionnaire (PHQ-9); a quality of recovery (QoR-15) form; and a numeric rating scale (NRS). Additional secondary outcomes included the levels of C-reactive protein (CRP) and interleukin 6 (IL-6) on postoperative days (PODs) 1, 3, and 5, the length of hospital stay, and opioid use throughout the hospital stay. Results: The scores of PHQ-9 and HAMD-17 in the S-ketamine group were lower than those in the placebo group on postoperative days (PODs) 1, 2, and 7 (p < 0.05). The scores of QoR-15 in the S-ketamine group were higher than those in the placebo group on postoperative days (PODs) 3 and 5 (p < 0.05). The NRS scores of PACU, postoperative days 1 and 2 in the S-ketamine group were lower than those in the placebo group (p < 0.05). There was no significant difference in the CRP and IL-6 levels on postoperative days (PODs) 1, 3, and 5, postoperative complications, and hospital stay between the two groups (p > 0.05). Conclusions: The trial indicated that the intraoperative administration of low-dose S-ketamine could alleviate mild-to-moderate depressive symptoms and postoperative pain in patients with Crohn's disease undergoing bowel resection without worsening their safety.

A Medicago truncatula lncRNA MtCIR1 negatively regulates response to salt stress.

MAIN CONCLUSION: A lncRNA MtCIR1 negatively regulates the response to salt stress in Medicago truncatula seed germination by modulating seedling growth and ABA metabolism and signaling by enhancing Na+ accumulation. Increasing evidence suggests that long non-coding RNAs (lncRNAs) are involved in the regulation of plant tolerance to varying abiotic stresses. A large number of lncRNAs that are responsive to abiotic stress have been identified in plants; however, the mechanisms underlying the regulation of plant responses to abiotic stress by lncRNAs are largely unclear. Here, we functionally characterized a salt stress-responsive lncRNA derived from the leguminous model plant M. truncatula, referred to as MtCIR1, by expressing MtCIR1 in Arabidopsis thaliana in which no such homologous sequence was observed. Expression of MtCIR1 rendered seed germination more sensitive to salt stress by enhanced accumulation of abscisic acid (ABA) due to suppressing the expression of the ABA catabolic enzyme CYP707A2. Expression of MtCIR1 also suppressed the expression of genes associated with ABA receptors and signaling. The ABA-responsive gene AtPGIP2 that was involved in degradation of cell wall during seed germination was up-regulated by expressing MtCIR1. On the other hand, expression of MtCIR1 in Arabidopsis thaliana enhanced foliar Na+ accumulation by down-regulating genes encoding Na+ transporters, thus rendering the transgenic plants more sensitive to salt stress. These results demonstrate that the M. truncatula lncRNA MtCIR1 negatively regulates salt stress response by targeting ABA metabolism and signaling during seed germination and foliar Na+ accumulation by affecting Na+ transport under salt stress during seedling growth. These novel findings would advance our knowledge on the regulatory roles of lncRNAs in response of plants to salt stress.

Reorganization of three-dimensional chromatin architecture in Medicago truncatula under phosphorus deficiency.

Emerging evidence reveals that the three-dimensional (3D) chromatin architecture plays a key regulatory role in various biological processes of plants. However, information on the 3D chromatin architecture of the legume model plant Medicago truncatula and its potential roles in the regulation of response to mineral nutrient deficiency are very limited. Using high-resolution chromosome conformation capture sequencing, we identified the 3D genome structure of M. truncatula in terms of A/B compartments, topologically associated domains (TADs) and chromatin loops. The gene density, expressional level, and active histone modification were higher in A compartments than in B compartments. Moreover, we analysed the 3D chromatin architecture reorganization in response to phosphorus (P) deficiency. The intra-chromosomal cis-interaction proportion was increased by P deficiency, and a total of 748 A/B compartment switch regions were detected. In these regions, density changes in H3K4me3 and H3K27ac modifications were associated with expression of P deficiency-responsive genes involved in root system architecture and hormonal responses. Furthermore, these genes enhanced P uptake and mobilization by increasing root surface area and strengthening signal transduction under P deficiency. These findings advance our understanding of the potential roles of 3D chromatin architecture in responses of plants in general, and in particular in M. truncatula, to P deficiency.