Differentiating low-risk thymomas from high-risk thymomas: preoperative radiomics nomogram based on contrast enhanced CT to minimize unnecessary invasive thoracotomy.

BACKGROUND: This study was designed to develop a combined radiomics nomogram to preoperatively predict the risk categorization of thymomas based on contrast-enhanced computed tomography (CE-CT) images. MATERIALS: The clinical and CT data of 178 patients with thymoma (100 patients with low-risk thymomas and 78 patients with high-risk thymomas) collected in our hospital from March 2018 to July 2023 were retrospectively analyzed. The patients were randomly divided into a training set (n = 125) and a validation set (n = 53) in a 7:3 ratio. Qualitative radiological features were recorded, including (a) tumor diameter, (b) location, (c) shape, (d) capsule integrity, (e) calcification, (f) necrosis, (g) fatty infiltration, (h) lymphadenopathy, and (i) enhanced CT value. Radiomics features were extracted from each CE-CT volume of interest (VOI), and the least absolute shrinkage and selection operator (LASSO) algorithm was performed to select the optimal discriminative ones. A combined radiomics nomogram was further established based on the clinical factors and radiomics scores. The differentiating efficacy was determined using receiver operating characteristic (ROC) analysis. RESULTS: Only one clinical factor (incomplete capsule) and seven radiomics features were found to be independent predictors and were used to establish the radiomics nomogram. In differentiating low-risk thymomas (types A, AB, and B1) from high-risk ones (types B2 and B3), the nomogram demonstrated better diagnostic efficacy than any single model, with the respective area under the curve (AUC), accuracy, sensitivity, and specificity of 0.974, 0.921, 0.962 and 0.900 in the training cohort, 0.960, 0.892, 0923 and 0.897 in the validation cohort, respectively. The calibration curve showed good agreement between the prediction probability and actual clinical findings. CONCLUSIONS: The nomogram incorporating clinical factors and radiomics features provides additional value in differentiating the risk categorization of thymomas, which could potentially be useful in clinical practice for planning personalized treatment strategies.

Deep learning-based automatic segmentation of meningioma from T1-weighted contrast-enhanced MRI for preoperative meningioma differentiation using radiomic features.

BACKGROUND: This study aimed to establish a dedicated deep-learning model (DLM) on routine magnetic resonance imaging (MRI) data to investigate DLM performance in automated detection and segmentation of meningiomas in comparison to manual segmentations. Another purpose of our work was to develop a radiomics model based on the radiomics features extracted from automatic segmentation to differentiate low- and high-grade meningiomas before surgery. MATERIALS: A total of 326 patients with pathologically confirmed meningiomas were enrolled. Samples were randomly split with a 6:2:2 ratio to the training set, validation set, and test set. Volumetric regions of interest (VOIs) were manually drawn on each slice using the ITK-SNAP software. An automatic segmentation model based on SegResNet was developed for the meningioma segmentation. Segmentation performance was evaluated by dice coefficient and 95% Hausdorff distance. Intra class correlation (ICC) analysis was applied to assess the agreement between radiomic features from manual and automatic segmentations. Radiomics features derived from automatic segmentation were extracted by pyradiomics. After feature selection, a model for meningiomas grading was built. RESULTS: The DLM detected meningiomas in all cases. For automatic segmentation, the mean dice coefficient and 95% Hausdorff distance were 0.881 (95% CI: 0.851-0.981) and 2.016 (95% CI:1.439-3.158) in the test set, respectively. Features extracted on manual and automatic segmentation are comparable: the average ICC value was 0.804 (range, 0.636-0.933). Features extracted on manual and automatic segmentation are comparable: the average ICC value was 0.804 (range, 0.636-0.933). For meningioma classification, the radiomics model based on automatic segmentation performed well in grading meningiomas, yielding a sensitivity, specificity, accuracy, and area under the curve (AUC) of 0.778 (95% CI: 0.701-0.856), 0.860 (95% CI: 0.722-0.908), 0.848 (95% CI: 0.715-0.903) and 0.842 (95% CI: 0.807-0.895) in the test set, respectively. CONCLUSIONS: The DLM yielded favorable automated detection and segmentation of meningioma and can help deploy radiomics for preoperative meningioma differentiation in clinical practice.

An n-Type Conjugated Polymer with Low Crystallinity for High-Performance Organic Thermoelectrics.

Conjugated polymers (CPs) with low crystallinity are promising candidates for application in organic thermoelectrics (OTEs), particularly in flexible devices, because the disordered structures of these CPs can effectively accommodate dopants and ensure robust resistance to bending. However, n-doped CPs usually exhibit poor thermoelectric performance, which hinders the development of high-performance thermoelectric generators. Herein, we report an n-type CP (ThDPP-CNBTz) comprising two acceptor units: a thiophene-flanked diketopyrrolopyrrole and a cyano-functionalized benzothiadiazole. ThDPP-CNBTz shows a low LUMO energy level of below -4.20 eV and features low crystallinity, enabling high doping efficiency. Moreover, the dual-acceptor design enhances polaron delocalization, resulting in good thermoelectric performance. After n-doping, ThDPP-CNBTz exhibits an average electrical conductivity (σ) of 50.6 S cm-1 and a maximum power factor (PF) of 126.8 µW m-1 K-2, which is among the highest values reported for solution-processed n-type CPs to date. Additionally, a solution-processed flexible OTE device based on doped ThDPP-CNBTz exhibits a maximum PF of 70 µW m-1 K-2; the flexible device also shows remarkable resistance to bending strain, with only a marginal change in σ after 600 bending cycles. The findings presented in this work will advance the development of n-type CPs for OTE devices, and flexible devices in particular.

An n-Type Open-Shell Conjugated Polymer with High-Spin Ground-State and High Intrinsic Electrical Conductivity.

Open-shell conjugated polymers with a high intrinsic conductivity and high-spin ground state hold considerable promise for applications in organic electronics and spintronics. Herein, two novel acceptor-acceptor (A-A) conjugated polymers based on a highly electron-deficient quinoidal benzodifurandione unit have been developed, namely DPP-BFDO-Th and DPP-BFDO. The incorporation of the quinoidal moiety into the polymers backbones enables deeply aligned lower-lying lowest unoccupied molecular orbital (LUMO) levels of below -4.0 eV. Notably, DPP-BFDO exhibits an exceptionally low LUMO (-4.63 eV) and a high-spin ground state characterized by strong diradical characters. Moreover, a self-doping through intermolecular charge-transfer is observed for DPP-BFDO, as evidenced by X-ray photoelectron spectroscopy (XPS) studies. The high carrier concentration in combination with a planar and linear conjugated backbone yields a remarkable electrical conductivity (σ) of 1.04 S cm-1 in the "undoped" native form, ranking among the highest values reported for n-type radical-based conjugated polymers. When employed as an n-type thermoelectric material, DPP-BFDO achieves a power factor of 12.59 µW m-1 K-2. Furthermore, upon n-doping, the σ could be improved to 65.68 S cm-1. This study underscores the great potential of electron-deficient quinoidal units in constructing dopant-free n-type conductive polymers with a high-spin ground state and exceptional intrinsic conductivity.

Protein kinase MtCIPK12 modulates iron reduction in Medicago truncatula by regulating riboflavin biosynthesis.

Iron (Fe) is an essential micronutrient, and deficiency in available Fe is one of the most important limiting factors for plant growth. In some species including Medicago truncatula, Fe deficiency results in accumulation of riboflavin, a response associated with Fe acquisition. However, how the plant's Fe status is integrated to tune riboflavin biosynthesis and how riboflavin levels affect Fe acquisition and utilization remains largely unexplored. We report that protein kinase CIPK12 regulates ferric reduction by accumulation of riboflavin and its derivatives in roots of M. truncatula via physiological and molecular characterization of its mutants and over-expressing materials. Mutations in CIPK12 enhance Fe accumulation and improve photosynthetic efficiency, whereas overexpression of CIPK12 shows the opposite phenotypes. The Calcineurin B-like proteins CBL3 and CBL8 interact with CIPK12, which negatively regulates the expression of genes encoding key enzymes in the riboflavin biosynthesis pathway. CIPK12 negatively regulates Fe acquisition by suppressing accumulation of riboflavin and its derivatives in roots, which in turn influences ferric reduction activity by riboflavin-dependent electron transport under Fe deficiency. Our findings uncover a new regulatory mechanism by which CIPK12 regulates riboflavin biosynthesis and Fe-deficiency responses in plants.

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.

Elevated ozone decreases the multifunctionality of belowground ecosystems.

Elevated tropospheric ozone (O3 ) affects the allocation of biomass aboveground and belowground and influences terrestrial ecosystem functions. However, how belowground functions respond to elevated O3 concentrations ([O3 ]) remains unclear at the global scale. Here, we conducted a detailed synthesis of belowground functioning responses to elevated [O3 ] by performing a meta-analysis of 2395 paired observations from 222 publications. We found that elevated [O3 ] significantly reduced the primary productivity of roots by 19.8%, 16.3%, and 26.9% for crops, trees and grasses, respectively. Elevated [O3 ] strongly decreased the root/shoot ratio by 11.3% for crops and by 4.9% for trees, which indicated that roots were highly sensitive to O3 . Elevated [O3 ] impacted carbon and nitrogen cycling in croplands, as evidenced by decreased dissolved organic carbon, microbial biomass carbon, total soil nitrogen, ammonium nitrogen, microbial biomass nitrogen, and nitrification rates in association with increased nitrate nitrogen and denitrification rates. Elevated [O3 ] significantly decreased fungal phospholipid fatty acids in croplands, which suggested that O3 altered the microbial community and composition. The responses of belowground functions to elevated [O3 ] were modified by experimental methods, root environments, and additional global change factors. Therefore, these factors should be considered to avoid the underestimation or overestimation of the impacts of elevated [O3 ] on belowground functioning. The significant negative relationships between O3 -treated intensity and the multifunctionality index for croplands, forests, and grasslands implied that elevated [O3 ] decreases belowground ecosystem multifunctionality.

Genome-wide analysis of the Glutathione S-Transferase family in wild Medicago ruthenica and drought-tolerant breeding application of MruGSTU39 gene in cultivated alfalfa.

KEY MESSAGE: Transformation of MruGSTU39 in M. ruthenica and alfalfa enhanced growth and survival of transgenic plants by up-regulating GST and glutathione peroxidase activity to detoxify ROS under drought stress. Glutathione S-transferases (GSTs) are ubiquitous supergene family which play crucial roles in detoxification of reactive oxygen species (ROS). Despite studies on GSTs, few studies have focused on them in perennial, wild plant species with high tolerance to environmental stress. Here, we identified 66 MruGST genes from the genome of Medicago ruthenica, a perennial legume species native to temperate grasslands with high tolerance to environmental stress. These genes were divided into eight classes based on their conserved domains, phylogenetic tree and gene structure, with the tau class being the most numerous. Duplication analysis revealed that GST family in M. ruthenica was expanded by segmental and tandem duplication. Several drought-responsive MruGSTs were identified by transcriptomic analyses. Of them, expression of MruGSTU39 was up-regulated much more in a tolerant accession by drought stress. Transformation of MruGSTU39 in M. ruthenica and alfalfa (Medicago sativa) enhanced growth and survival of transgenic seedlings than their wild-type counterparts under drought. We demonstrated that MruGSTU39 can detoxify ROS to reduce its damage to membrane by up-regulating activities of GST and glutathione peroxidase. Our findings provide full-scale knowledge on GST family in the wild legume M. ruthenica with high tolerance to drought, and highlight improvement tolerance of legume forages to drought using genomic information of M. ruthenica.

A deep learning radiomics model may help to improve the prediction performance of preoperative grading in meningioma.

PURPOSE: This study aimed to investigate the clinical usefulness of the enhanced-T1WI-based deep learning radiomics model (DLRM) in differentiating low- and high-grade meningiomas. METHODS: A total of 132 patients with pathologically confirmed meningiomas were consecutively enrolled (105 in the training cohort and 27 in the test cohort). Radiomics features and deep learning features were extracted from T1 weighted images (T1WI) (both axial and sagittal) and the maximum slice of the axial tumor lesion, respectively. Then, the synthetic minority oversampling technique (SMOTE) was utilized to balance the sample numbers. The optimal discriminative features were selected for model building. LightGBM algorithm was used to develop DLRM by a combination of radiomics features and deep learning features. For comparison, a radiomics model (RM) and a deep learning model (DLM) were constructed using a similar method as well. Differentiating efficacy was determined by using the receiver operating characteristic (ROC) analysis. RESULTS: A total of 15 features were selected to construct the DLRM with SMOTE, which showed good discrimination performance in both the training and test cohorts. The DLRM outperformed RM and DLM for differentiating low- and high-grade meningiomas (training AUC: 0.988 vs. 0.980 vs. 0.892; test AUC: 0.935 vs. 0.918 vs. 0.718). The accuracy, sensitivity, and specificity of the DLRM with SMOTE were 0.926, 0.900, and 0.924 in the test cohort, respectively. CONCLUSION: The DLRM with SMOTE based on enhanced T1WI images has favorable performance for noninvasively individualized prediction of meningioma grades, which exhibited favorable clinical usefulness superior over the radiomics features.

The genome of a wild Medicago species provides insights into the tolerant mechanisms of legume forage to environmental stress.

BACKGROUND: Medicago ruthenica, a wild and perennial legume forage widely distributed in semi-arid grasslands, is distinguished by its outstanding tolerance to environmental stress. It is a close relative of commonly cultivated forage of alfalfa (Medicago sativa). The high tolerance of M. ruthenica to environmental stress makes this species a valuable genetic resource for understanding and improving traits associated with tolerance to harsh environments. RESULTS: We sequenced and assembled genome of M. ruthenica using an integrated approach, including PacBio, Illumina, 10×Genomics, and Hi-C. The assembled genome was 904.13 Mb with scaffold N50 of 99.39 Mb, and 50,162 protein-coding genes were annotated. Comparative genomics and transcriptomic analyses were used to elucidate mechanisms underlying its tolerance to environmental stress. The expanded FHY3/FAR1 family was identified to be involved in tolerance of M. ruthenica to drought stress. Many genes involved in tolerance to abiotic stress were retained in M. ruthenica compared to other cultivated Medicago species. Hundreds of candidate genes associated with drought tolerance were identified by analyzing variations in single nucleotide polymorphism using accessions of M. ruthenica with varying tolerance to drought. Transcriptomic data demonstrated the involvements of genes related to transcriptional regulation, stress response, and metabolic regulation in tolerance of M. ruthenica. CONCLUSIONS: We present a high-quality genome assembly and identification of drought-related genes in the wild species of M. ruthenica, providing a valuable resource for genomic studies on perennial legume forages.

Plant 3D Chromatin Organization: Important Insights from Chromosome Conformation Capture Analyses of the Last 10 Years.

Over the past few decades, eukaryotic linear genomes and epigenomes have been widely and extensively studied for understanding gene expression regulation. More recently, the three-dimensional (3D) chromatin organization was found to be important for determining genome functionality, finely tuning physiological processes for appropriate cellular responses. With the development of visualization techniques and chromatin conformation capture (3C)-based techniques, increasing evidence indicates that chromosomal architecture characteristics and chromatin domains with different epigenetic modifications in the nucleus are correlated with transcriptional activities. Subsequent studies have further explored the intricate interplay between 3D genome organization and the function of interacting regions. In this review, we summarize spatial distribution patterns of chromatin, including chromatin positioning, configurations and domains, with a particular focus on the effect of a unique form of interaction between varieties of factors that shape the 3D genome conformation in plants. We further discuss the methods, advantages and limitations of various 3C-based techniques, highlighting the applications of these technologies in plants to identify chromatin domains, and address their dynamic changes and functional implications in evolution, and adaptation to development and changing environmental conditions. Moreover, the future implications and emerging research directions of 3D genome organization are discussed.

Artemether Attenuates Aß25-35-Induced Cognitive Impairments by Downregulating Aß, BACE1, mTOR and Tau Proteins.

BACKGROUND: Alzheimer's disease (AD) is clinically characterized as a progressive cognitive impairment and behavioral disorder. Pathological hallmarks of AD include extracellular senile plaques (SPs), intracellular neurofibrillary tangles (NFTs) and massive neuronal loss. Although the exact cause of AD is not well understood, a mounting body of evidence has demonstrated that the pathogenesis of AD is associated with oxidative stress, neu-roinflammation, and amyloid beta (Aß) induced neural apoptosis. Moreover, overexpression of ß-secretase 1 (BACE1), Aß, mammalian target of rapamycin (mTOR), and Tau proteins are closely related to cognitive symptoms in AD. Studies have demonstrated that artemether, an antimalarial drug with acceptable side effects, possesses protective effects against neuroinflammation and oxidative stress. Importantly, artemether can easily penetrate the blood brain barrier, thereby representing an ideal drug candidate for AD treatment. METHODS: The effect of artemether on memory protection and the associated molecular mechanisms were investigated in an Aß25-35 induced cognitive impairments rat model. RESULTS: Results of the in vivo study showed that oral administration of artemether significantly attenuated Aß25-35-induced cognitive impairment in rats. Results of the in vitro study revealed that artemether significantly downregulated the endogenous expression of Aß, BACE1, mTOR, and Tau proteins in N2a cells. CONCLUSIONS: The beneficial effect of artemether against Aß 25-35-induced cognitive impairments was attributable to the downregulation of the expression of Aß, BACE1, mTOR, and Tau proteins, suggesting the potential of artemether as an effective, neuronal protective, and multi-targeted drug candidate for AD treatment.

Metabolic response of soybean leaves induced by short-term exposure of ozone.

The ever-increasing ozone (O3) concentration has led to reduced production and altered quality of soybean. Abundant reports have explored the damage mechanisms of O3 on soybean. However, how the elevated O3 affects metabolite profiling of soybean remains to be poorly understood. Here, we compare the metabolic profile of soybean leaves under charcoal filtered air (CF, <20 ppb) and short-term elevated O3 concentration (EO, 100 ppb). High level of O3 affects metabolites for the tricarbonic acid (TCA) cycle, reactive oxygen species, cell wall composition and amino acids. Significantly, jasmonic acid-related metabolite promoting stomata closure is highly induced with 125-fold change. Furthermore, O3 fumigation alters the expression of genes contributing to the biosynthesis of certain metabolites in TCA cycle. Together, these findings identify a wide range of changed metabolites in response to O3 pollution. Our results pave the way for the genetic improvement of soybean to adapt to O3 pollution to maintain stable yields.

Assessing the effects of elevated ozone on physiology, growth, yield and quality of soybean in the past 40 years: A meta-analysis.

Soybean (Glycine max) production is seriously threatened by ground-level ozone (O3) pollution. The goal of our study is to summarize the impacts of O3 on physiology, growth, yield, and quality of soybean, as well as root parameters. We performed meta-analysis on the collated 48 peer-reviewed papers published between 1980 and 2019 to quantitatively summarize the response of soybean to elevated O3 concentrations ([O3]). Relative to charcoal-filtered air (CF), elevated [O3] significantly accelerated chlorophyll degradation, enhanced foliar injury, and inhibited growth of soybean, evidenced by great reductions in leaf area (-20.8%), biomass of leaves (-13.8%), shoot (-22.8%), and root (-16.9%). Shoot of soybean was more sensitive to O3 than root in case of biomass. Chronic ozone exposure of about 75.5 ppb posed pronounced decrease in seed yield of soybean (-28.3%). In addition, root environment in pot contributes to higher reduction in shoot biomass and yield of soybean. Negative linear relationships were observed between yield loss and intensity of O3 treatment, AOT40. The larger loss in seed yield was significantly associated with higher reduction in shoot biomass and other yield component. This meta-analysis demonstrates the effects of elevated O3 on soybean were pronounced, suggesting that O3 pollution is still a soaring threat to the productivity of soybean in regions with high ozone levels.

Identification of tissue-specific and cold-responsive lncRNAs in Medicago truncatula by high-throughput RNA sequencing.

BACKGROUND: Long non-coding RNAs (lncRNAs) play important roles in the regulation of plant responses to environmental stress by acting as essential regulators of gene expression. However, whether and how lncRNAs are involved in cold acclimation-dependent freezing tolerance in plants remains largely unknown. Medicago truncatula is a prominent model for studies of legume genomics, and distinguished by its cold-acclimation characteristics. To determine the roles of lncRNAs in plant cold stress response, we conducted genome-wide high-throughput sequencing in the legume model plant M. truncatula. RESULTS: RNA-seq data were generated from twelve samples for the four treatments, i.e., non-cold treated leaves and roots, cold-treated leaves and roots of M. truncatula Jemalong A17 seedlings. A total of 1204 million raw reads were generated. Of them, 1150 million filtered reads after quality control (QC) were subjected to downstream analysis. A large number of 24,368 unique lncRNAs were identified from the twelve samples. Among these lncRNAs, 983 and 1288 were responsive to cold treatment in the leaves and roots, respectively. We further found that the intronic-lncRNAs were most sensitive to the cold treatment. The cold-responsive lncRNAs were unevenly distributed across the eight chromosomes in M. truncatula seedlings with obvious preferences for locations. Further analyses revealed that the cold-responsive lncRNAs differed between leaves and roots. The putative target genes of the lncRNAs were predicted to mainly involve the processes of protein translation, transport, metabolism and nucleic acid transcription. Furthermore, the networks of a tandem array of CBF/DREB1 genes that were reported to be located in a major freezing tolerance QTL region on chromosome 6 and their related lncRNAs were dissected based on their gene expression and chromosome location. CONCLUSIONS: We identified a comprehensive set of lncRNAs that were responsive to cold treatment in M. truncatula seedlings, and discovered tissue-specific cold-responsive lncRNAs in leaves and roots. We further dissected potential regulatory networks of CBF Intergenic RNA (MtCIR1) and MtCBFs that play critical roles in response and adaptation of M. truncatula to cold stress.

Assessment of high sensitivity C-reactive protein and coronary plaque characteristics by computed tomography in patients with and without diabetes mellitus.

BACKGROUND: To evaluate the coronary plaque characteristics of coronary arteries using computed tomography angiography (CTA) in order to assess the risk of coronary artery disease and the relevance of high sensitivity C reactive protein (hs-CRP) in patients with Diabetes Mellitus (DM). METHODS: The clinical data of 400 DM patients and 400 non-DM patients from January 2017 to December 2019 were collected, including the results of coronaryCTA. The plasma hs-CRP level of the two groups were divided into three groups: CRP ≤ 1, 1 < CRP ≤ 2, CRP > 2. The correlation of the degree of stenosis, the number of plaques, the nature of plaques and hs-CRP value between the two groups was evaluated. RESULTS: Compared with non-DM patients, the incidence of coronary artery plaques and lumen stenosis in DM patients was more higher than that in non-DM patients. DM patients were more likely to have more diseased vessels, especially diffuse vascular disease (12.00% vs 1.75%; P < 0.001). Subjects with high hs-CRP levels were more likely to have any plaque compared with individuals showing normal hs-CRP levels (p<0.01). There was no statistical significance in non calcified plaque with high level of hs-CRP, but the occurrence of plaque types in DM group was statistically significant compared with other hs-CRP levels in non DM group. Subjects with high hs-CRP were observed to be at increased risk for the presence of calcified plaque and severe narrowing in the unadjusted values. CONCLUSIONS: Coronary CTA combined with hs-CRP can accurately detect the characteristics of coronary artery stenosis and plaque in DM patients, which has an important clinical value in the risk assessment of coronary heart disease in DM patients.

The Adaptive Mechanism of Plants to Iron Deficiency via Iron Uptake, Transport, and Homeostasis.

Iron is an essential element for plant growth and development. While abundant in soil, the available Fe in soil is limited. In this regard, plants have evolved a series of mechanisms for efficient iron uptake, allowing plants to better adapt to iron deficient conditions. These mechanisms include iron acquisition from soil, iron transport from roots to shoots, and iron storage in cells. The mobilization of Fe in plants often occurs via chelating with phytosiderophores, citrate, nicotianamine, mugineic acid, or in the form of free iron ions. Recent work further elucidates that these genes' response to iron deficiency are tightly controlled at transcriptional and posttranscriptional levels to maintain iron homeostasis. Moreover, increasing evidences shed light on certain factors that are identified to be interconnected and integrated to adjust iron deficiency. In this review, we highlight the molecular and physiological bases of iron acquisition from soil to plants and transport mechanisms for tolerating iron deficiency in dicotyledonous plants and rice.

Novel phosphate deficiency-responsive long non-coding RNAs in the legume model plant Medicago truncatula.

Emerging evidence indicates that long non-coding RNAs (lncRNAs) play important roles in the regulation of many biological processes. Inhibition of plant growth due to deficiency in soil inorganic phosphate (Pi) occurs widely across natural and agricultural ecosystems; however, we know little about the function of plant lncRNAs in response to Pi deficiency. To address this issue, we first identified 10 785 lncRNAs in the legume model species Medicago truncatula by sequencing eight strand-specific libraries. Out of these lncRNAs, 358 and 224 were responsive to Pi deficiency in the leaves and roots, respectively. We further predicted and classified the putative targets of those lncRNAs and the results revealed that they may be involved in the processes of signal transduction, energy synthesis, detoxification, and Pi transport. Finally, we functionally characterized three Phosphate Deficiency-Induced LncRNAs (PDILs) using their corresponding Tnt1 mutants. The results showed that PDIL1 suppressed degradation of MtPHO2, which encodes a ubiquitin-conjugating E2 enzyme regulated by miR399, while PDIL2 and PDIL3 directly regulated Pi transport at the transcriptional level. These findings demonstrate that PDILs can regulate Pi-deficiency signaling and Pi transport, highlighting the involvement of lncRNAs in the regulation of responses of plants to Pi deficiency.

A novel soil manganese mechanism drives plant species loss with increased nitrogen deposition in a temperate steppe.

Loss of plant diversity with increased anthropogenic nitrogen (N) deposition in grasslands has occurred globally. In most cases, competitive exclusion driven by preemption of light or space is invoked as a key mechanism. Here, we provide evidence from a 9-yr N-addition experiment for an alternative mechanism: differential sensitivity of forbs and grasses to increased soil manganese (Mn) levels. In Inner Mongolia steppes, increasing the N supply shifted plant community composition from grass-forb codominance (primarily Stipa krylovii and Artemisia frigida, respectively) to exclusive dominance by grass, with associated declines in overall species richness. Reduced abundance of forbs was linked to soil acidification that increased mobilization of soil Mn, with a 10-fold greater accumulation of Mn in forbs than in grasses. The enhanced accumulation of Mn in forbs was correlated with reduced photosynthetic rates and growth, and is consistent with the loss of forb species. Differential accumulation of Mn between forbs and grasses can be linked to fundamental differences between dicots and monocots in the biochemical pathways regulating metal transport. These findings provide a mechanistic explanation for N-induced species loss in temperate grasslands by linking metal mobilization in soil to differential metal acquisition and impacts on key functional groups in these ecosystems.

Identification and characterization of long non-coding RNAs involved in osmotic and salt stress in Medicago truncatula using genome-wide high-throughput sequencing.

BACKGROUND: Long non-coding RNAs (lncRNAs) have been shown to play crucially regulatory roles in diverse biological processes involving complex mechanisms. However, information regarding the number, sequences, characteristics and potential functions of lncRNAs in plants is so far overly limited. RESULTS: Using high-throughput sequencing and bioinformatics analysis, we identified a total of 23,324 putative lncRNAs from control, osmotic stress- and salt stress-treated leaf and root samples of Medicago truncatula, a model legume species. Out of these lncRNAs, 7,863 and 5,561 lncRNAs were identified from osmotic stress-treated leaf and root samples, respectively. While, 7,361 and 7,874 lncRNAs were identified from salt stress-treated leaf and root samples, respectively. To reveal their potential functions, we analyzed Gene Ontology (GO) terms of genes that overlap with or are neighbors of the stress-responsive lncRNAs. Enrichments in GO terms in biological processes such as signal transduction, energy synthesis, molecule metabolism, detoxification, transcription and translation were found. CONCLUSIONS: LncRNAs are likely involved in regulating plant's responses and adaptation to osmotic and salt stresses in complex regulatory networks with protein-coding genes. These findings are of importance for our understanding of the potential roles of lncRNAs in responses of plants in general and M. truncatula in particular to abiotic stresses.