Model Plant Research Articles

Arabidopsis thaliana argininosuccinate lyase structure uncovers the role of serine as the catalytic base

Arginine is an important amino acid in plants, as it not only plays a structural role and serves as nitrogen storage but is also a precursor for various molecules, including polyamines and proline. Arginine is produced by argininosuccinate lyase (ASL) which catalyzes the cleavage of argininosuccinate to arginine and fumarate. ASL belongs to the fumarate lyase family and while many members of this family were well-characterized, little is known about plant ASLs. Here we present the first crystal structures of ASL from the model plant, Arabidopsis thaliana (AtASL). One of the structures represents the unliganded form of the AtASL homotetramer. The other structure, obtained from a crystal soaked in argininosuccinate, accommodates the substrate or the reaction products in one of four active sites of the AtASL tetramer. Each active site is located at the interface of three neighboring protomers. The AtASL structure with ligands allowed us to analyze the enzyme-substrate and the enzyme-product interactions in detail. Furthermore, based on our analyses, we describe residues of AtASL crucial for catalysis. The structure of AtASL gives the rationale for the open-to-close transition of the GSS mobile loop and indicates the importance of serine 333 from this loop for the enzymatic action of the enzyme. Finally, we supplemented the structural data with the identification of sequence motifs characteristic for ASLs.

Genome-wide DNA methylation and their transgenerational pattern differ in Arabidopsis thaliana populations originated along the elevation of West Himalaya

Methylation at 5' cytosine of DNA molecule is an important epigenetic mark. It is known to play critical role in adaptation of organisms under different biotic and abiotic stressors via modulating gene expression and/or chromatin architecture. Plant populations evolved under variable climatic conditions may have evolved different epigenetic marks including DNA methylation. Here we, describe the genome-wide DNA methylation pattern under native field, F1 and F6 generation followed by their association with phenotypes, climate and global gene expression in the three Arabidopsis thaliana populations originated at different elevation ranges of Indian West Himalaya. We show that the global methyl cytosine (mC) content is more or less similar in the three populations but differ in their distribution across genome. There was an increase in differential methylation between the populations as elevation increased. The methylation divergence was the highest between the low and the high elevation populations. The high elevation populations were hypo-methylated than the low elevation population. The methylation in the genes was associated with population specific phenotypes and climate of the region. The genes which were differentially methylated as well as differentially expressed between the low and high elevation populations were mostly related to abiotic stresses. When grown under controlled condition, there was gain of differential methylation over native condition and the maximum percent changes was observed in CHH-sequence context. Further ~ 99.8% methylated cytosines were stably passed on from F1 to F6 generation. Overall, our data suggest that high elevation population is epigenetically more plastic under changing environmental condition.BackgroundArabidopsis thaliana is the model plant species and has been extensively studied to understand plants life processes. There are numerous reports on its origin, demography, evolution, epigenomes and adaptation etc. however, Indian populations of Arabidopsis thaliana evolved along wide elevation ranging from ~ 700 m amsl to ~ 3400 m amsl not explored yet. Here we, describe the genome-wide DNA methylation pattern under native field, F1 and F6 generation followed by their association with phenotypes, climate and global gene expression in the three Arabidopsis thaliana populations originated at different elevation ranges of Indian West Himalaya.Results In our study we found that total mCs percent was more or less similar in the three populations but differ in their distribution across genome. The proportion of CG-mCs was the highest, followed by CHH-mCs and CHG-mCs in all the three populations. Under native field condition the methylation divergence was more prominent between low and high elevation populations and the high elevation populations were hypo-methylated than the low elevation population. The methylation in the genes was linked to population-specific phenotypes and the regional climate. The genes that showed differential methylation and expression between low and high elevation populations were primarily associated with abiotic stress responses. When grown under controlled condition, there was gain of differential methylation compared to the native condition and the maximum percent changes was observed in CHH-sequence context. Further 99.8% methylated cytosines were stably passed on from F1 to F6 generation.Conclusions The populations of A. thaliana adapted at different climatic conditions were significantly differentially methylated both under native and controlled condition. However, the magnitude and extent of gain or loss of methylation were most significant between the low and the high elevation populations. Overall, our data suggest that high elevation population is epigenetically more plastic under changing environmental condition.

Sodium alginate-g-polyacrylamide hydrogel for water retention and plant growth promotion in water-deficient soils

Natural polymer-based hydrogels are preferred as soil water retention agents due to their inherent biocompatibility and biodegradability. Generally, these natural polymers are chemically modified by graft polymerization of vinyl monomers to improve their water absorption and retention properties. Among the polysaccharides used to prepare natural hydrogels, those based on sodium alginate (Alg) stand out for their high-water absorption and retention capacity, as well as for their ability to promote plant growth. The main objective of this study was to develop a biodegradable alginate-based hydrogel as a water retainer to promote plant growth under water deficit conditions. The synthesis was achieved by grafting poly(acrylamide) (PAM) onto Alg backbone, using bisacrylamide as chemical crosslinker and different ratios of alginate:acrylamide (Ac). In addition, Eucalyptus nitens seedlings were used as a model plant to evaluate the effect of alginate-g-polyacrylamide (Alg:PAM) hydrogel application to the growing medium on plant survival, growth, and physiological responses under both well-watered and water-deficient soil conditions. The maximum degree of swelling (65 g/g) was obtained for the hydrogel prepared. The pseudo-second order model described the water uptake kinetics of the hydrogel. The degradability of Alg:PAM hydrogel reached up to 85 % in 5 weeks in soil and occurs by breaking the glycosidic bonds of the alginate. The E. nitens seedlings cultivated with different doses of Alg:PAM hydrogel (4:1 Alg:Ac) showed higher values of height and root diameter relative growth, survival and photosynthetic responses in comparison to non-treated plants. The results indicate that Alg:PAM hydrogel (4:1 Alg:Ac) has promising applications in forestry as a water retention and seedling growth promoter under water deficient conditions.

Transcriptomic insights into mycorrhizal interactions with tomato root: a comparative study of short- and long-term post-inoculation responses.

Arbuscular mycorrhiza (AM) refers to a symbiotic association between plant roots and fungi that enhances the uptake of mineral nutrients from the soil and enables the plant to tolerate abiotic and biotic stresses. Although previously reported RNA-seq analyses have identified large numbers of AM-responsive genes in model plants, such as Solanum lycopersicum L., further studies are underway to comprehensively understand the complex interactions between plant roots and AM, especially in terms of the short- and long-term responses after inoculation. Herein, we used RNA-seq technology to obtain the transcriptomes of tomato roots inoculated with the fungus Rhizophagus irregularis at 7 and 30days post inoculation (dpi). Of the 1,019 differentially expressed genes (DEGs) in tomato roots, 635 genes showed differential expressions between mycorrhizal and non-mycorrhizal associations at the two time points. The number of upregulated DEGs far exceeded the number of downregulated ones at 7 dpi, and this difference decreased at 30dpi. Several notable genes were particularly involved in the plant defense, plant growth and development, ion transport, and biological processes, namely, GABAT, AGP, POD, NQO1, MT4, MTA, and AROGP3. In addition, the Kyoto encyclopedia of genes and genomes pathway enrichment analysis revealed that some of the genes were involved in different pathways, including those of ascorbic acid (AFRR, GME1, and APX), metabolism (CYP, GAPC2, and CAM2), and sterols (CYC1 and HMGR), as well as genes related to cell division and cell cycle (CDKB2 and PCNA). These findings provide valuable new data on AM-responsive genes in tomato roots at both short- and long-term postinoculation stages, enabling the deciphering of biological interactions between tomato roots and symbiotic fungi.

Design of LQ regulators with prescribed degree of stability for dual-rate systems based on reinforcement learning

This paper considers dual-rate systems, where the output is measured at a relatively slow rate while the control signal is adjusted at a faster rate. The output sampling time is an integer multiple of the input sampling time. The paper examines dual-rate inferential control systems, which consist of a fast model, a slow model, and a switch. Missing output samples are estimated using the fast single-rate model. The single-rate control algorithm is then implemented at the fast-sampling rate. The fast-sampling discrete-time model is derived from the plant’s continuous-time model using the first-order hold (FOH) element. A discrete LQ regulator is proposed for this plant model, with a prescribed degree of stability (all closed-loop eigenvalues are within the range 0 < λ < 1 in magnitude). The matrix gain is calculated offline, and an online method for calculating the regulator gain is provided. The regulator gain is calculated using policy iteration, specifically Hewer’s algorithm. Finally, it is demonstrated that the presented inferential control system remains effective in the presence of multiplicative unmodeled dynamics. The main contributions of the paper are: (i) Designing the LQ regulator with a prescribed degree of stability using reinforcement learning (RL) (generalized policy iteration); and (ii) Considering the robust stability of the inferential control system in the presence of multiplicative unmodeled dynamics using the lifting technique.

Quantitative and spatially resolved detection of multiplexed microRNA from plant tissue via hybridization to hydrogel-bound DNA probes in nanoliter well arrays

Understanding complex regulatory networks in plant systems requires elucidating the roles of various gene regulators under a spatial landscape. MicroRNA are key regulators that impart high information value through their tissue specificity and stability when using expression patterns for evaluating network outcomes. However, current techniques that utilize spatial multiplexing and quantitation of microRNA are limited to primarily mammalian systems. Here, we present a method to spatially resolve and quantify multiple endogenous microRNA in situ using ethanol fixed, paraffin embedded model plant species. This method utilizes target-specific microRNA capture along with universal ligating and labelling, all within functionalized hydrogel posts containing DNA probes in nanoliter well arrays. We demonstrate the platform’s multiplexing capabilities through analyzing three endogenous microRNA in Arabidopsis thaliana rosettes which provide useful answers to fundamental plant growth and development from the unique expression patterns. The spatial tissue technique is also validated using non-spatial small RNA assays to demonstrate the versatility of the well array platform. Our new platform expands the toolkit of spatial omics technologies for plants.

Optimizing Science Process Skills Through the Use of Simple Steam Power Plant Models in Middle School Physics Education

This study aims to evaluate the effectiveness of using a simple steam power plant prop in improving the science process skills of eighth grade students at Pesantren Guppi Samata Junior High School. The importance of this study lies in the need for innovative teaching methods that can improve students' engagement and understanding in science education, especially considering the limitations of traditional laboratory resources. A quasi-experimental design with a pretest-posttest control group was used, involving purposive sampling of two groups: an experimental group that used a simple steam power plant prop and a control group that did not use the prop. Data were collected through a structured multiple-choice test that assessed various aspects of science process skills and were analyzed using descriptive statistics, normality tests, and independent t-tests. The findings showed that the experimental group significantly outperformed the control group in the posttest (p = 0.000), indicating that the simple steam power plant prop effectively facilitates better understanding of scientific concepts through hands-on learning. The novelty of this study lies in its focus on the use of simple and accessible teaching props to improve practical skills in science education. The results of this study suggest that incorporating these tools into teaching can improve educational outcomes, and offer a valuable resource for educators facing limited laboratory facilities.

EcoFAB 3.0: a sterile system for studying sorghum that replicates previous field and greenhouse observations.

Studying plant-microbe interactions is one of the key elements in understanding the path to sustainable agricultural practices. These interactions play a crucial role in ensuring survival of healthy plants, soil and microbial communities. Many platforms have been developed over the years to isolate these highly complex interactions however, these are designed for small model plants. This creates a need for complementary devices for larger plants, such as sorghum. This work introduces a novel platform, EcoFAB 3.0, which is designed to enable studying bioenergy plants such as sorghum for up to 4 weeks in a controlled sterile environment. Several other advantages of this platform such as dark root chambers and user-friendly assembly are also discussed in this work. EcoFAB 3.0 was found to replicate previous greenhouse and field observations when comparing an engineered sorghum line overproducing 4-hydroxybenzoic acid (4-HBA) and wildtype (variety BTx430). Consistent with greenhouse and field observations, it was found that the engineered line of sorghum grown in EcoFAB 3.0 had a higher 4-HBA content and a lower dry biomass.

Agrobacterium-mediated Cuscuta campestris transformation as a tool for understanding plant-plant interactions.

Cuscuta campestris, a stem parasitic plant, has served as a valuable model plant for the exploration of plant-plant interactions and molecular trafficking. However, a major barrier to C. campestris research is that a method to generate stable transgenic plants has not yet been developed. Here, we describe the development of a Cuscuta transformation protocol using various reporter genes (GFP, GUS, or RUBY) and morphogenic genes (CcWUS2 and CcGRF/GIF), leading to a robust protocol for Agrobacterium-mediated C. campestris transformation. The stably transformed and regenerated RUBY C. campestris plants produced haustoria, the signature organ of parasitic plants, and these were functional in forming host attachments. The locations of T-DNA integration in the parasite genome were confirmed through TAIL-PCR. Transformed C. campestris also produced flowers and viable transgenic seeds exhibiting betalain pigment, providing proof of germline transmission of the RUBY transgene. Furthermore, RUBY is not only a useful selectable marker for the Agrobacterium-mediated transformation, but may also provide insight into the movement of molecules from C. campestris to the host during parasitism. Thus, the protocol for transformation of C. campestris reported here overcomes a major obstacle to Cuscuta research and opens new possibilities for studying parasitic plants and their interactions with hosts.

Use of CRISPR Technology in Gene Editing for Tolerance to Biotic Factors in Plants: A Systematic Review.

The objective of this systematic review (SR) was to select studies on the use of gene editing by CRISPR technology related to plant resistance to biotic stresses. We sought to evaluate articles deposited in six electronic databases, using pre-defined inclusion and exclusion criteria. This SR demonstrates that countries such as China and the United States of America stand out in studies with CRISPR/Cas. Among the most studied crops are rice, tomatoes and the model plant Arabidopsis thaliana. The most cited biotic agents include the genera, Xanthomonas, Manaporthe, Pseudomonas and Phytophthora. This SR also identifies several CRISPR/Cas-edited genes and demonstrates that plant responses to stressors are mediated by many complex signaling pathways. The Cas9 enzyme is used in most articles and Cas12 and 13 are used as additional editing tools. Furthermore, the quality of the articles included in this SR was validated by a risk of bias analysis. The information collected in this SR helps to understand the state of the art of CRISPR/Cas aimed at improving resistance to diseases and pests to understand the mechanisms involved in most host-pathogen relationships. This SR shows that the CRISPR/Cas system provides a straightforward method for rapid gene targeting, providing useful information for plant breeding programs.

Feedback control for plants with time delay

Abstract The paper considers the problem of feedback control design for plants with time delay. The role of the feedback is presented showing its ability to restrict the uncertainty in the plant model. The conditional feedback control structure is introduced and its properties for restricting model uncertainty are discussed. The presence of local feedback makes the conditional feedback structure pertinent for its usage when the plant contains a time delay element. The time delay model is replaced by its Pade series approximation. The key idea is to consider the time delay model as perturbation around its Pade series approximation. This fact allows utilizing the rational function expression in the procedure of controller design, thus avoiding using the irrational function of the time delay for this purpose. It is shown that the conditional feedback control structure gives an alternative than the Smith predictor method for controller design of plants with time delay e −θs in their structure. The efficiency of the presented method is demonstrated by a numerical example.

Phytotoxic and Cytogenetic Assessment of Glycerol Triazole Derivatives in Model Plants and Weeds.

Weed invasion represents a challenge for farmers, who typically manage it with herbicides. However, this approach raises concerns about environmental and human health, as well as increasing resistance in these plants with continued use. Therefore, exploring alternative methods, such as heterocyclic compounds, triazoles, is essential due to their biological and environmental relevance. This study aimed to evaluate the effects of twelve 1,2,3-triazoles on the germination and early development of Lactuca sativa, Bidens pilosa, and Lolium multiflorum, as well as their impact on cell division in the cells of L. sativa. Triazole derivatives 4a, 4b, 4c, 4g, 4h, 4i, 4k, and 4l exhibited phytotoxicity, showing varying levels of inhibition in germination, germination speed index, and root growth. Chlorinated compounds were the most detrimental to lettuce development. B. pilosa was notably affected by compounds 4h, 4i, 4k, and 4l, while L. multiflorum responded most to triazoles 4c and 4l, with effectiveness comparable to that of the herbicide glyphosate. All derivatives, except 4l, exhibited aneugenic mechanisms of action, and 4a, 4b, 4c, 4e, 4f, and 4g showed clastogenic effects. This study demonstrated the potential of triazoles as effective agents against weed growth, with mechanisms that warrant further investigation for agricultural applications.

Transcriptional and genetic characteristic of chimera pea generation via double ethyl methanesulfonate-induced mutation revealed by transcription analysis.

Ethyl methanesulfonate (EMS)-induced mutagenesis is a prominent method for generating plant mutants, often resulting in chimera plants; however, their transcriptional and genetic characteristic remain elusive. In this investigation, chimera pea (Pisum sativum L.) specimens, labeled GY1 and GY2, exhibiting a distinctive phenotype with yellow and green leaves were meticulously cultivated via sequential double EMS mutagenesis. The observed color disparity between the yellow and green leaves was attributed to a significant reduction in chlorophyll content coupled with heightened lutein levels in both chimeric variants. Transcriptome profiling revealed the enrichment of differentially expressed genes in both GY1 and GY2, specifically implicating Kyoto Encyclopedia of Genes and Genomes pathways linked to amino acid biosynthesis and ribosome development, alongside Gene Ontology (GO) biological processes linked with stress response mechanisms. Few structural genes associated with chlorophyll and lutein biosynthesis exhibited discernible differential expression. Despite these functional similarities, distinctive nuances were evident between specimens, with GY1 exhibiting enrichment in GO pathways related to chloroplast development and GY2 showing enrichment for ribosome development pathways. Single-nucleotide polymorphism (SNP) analysis uncovered a shared pool of 599 and 598 polymorphisms in the yellow and green leaves of GY1 and GY2, respectively, likely stemming from the initial EMS mutagenesis step. Further investigation revealed an increased number of unique SNPs in the yellow leaves following the second EMS application, whereas the green leaves exhibited sparse and unique SNP occurrences, suggestive of potential evasion from secondary mutagenesis. This inherent genetic variability underpins the mechanism underlying the formation of chimera plants. Predominant base mutations induced by EMS were characterized by G/A and C/T transitions, constituting 74.1% of the total mutations, aligning with established EMS mutation induction paradigms. Notably, genes encoding the eukaryotic translation initiation factor eIIso4G and the ubiquitin ligase RKP, known to modulate leaf color in model plants, harbored two SNPs in the yellow leaves of both GY1 and GY2, implicating their putative role in the yellow leaf phenotype. Collectively, this study provides novel insights into the transcriptional and genetic characteristics of chimera plants via EMS-induced mutagenesis.

A research and application of a digital failure knowledge model for nuclear power plant

Abstract The accumulation and application of knowledge about equipment component failures in nuclear power plant unit systems is an important way for domestic and foreign nuclear power plants to improve unit availability and economic benefits. Based on the existing equipment component knowledge models in China and the experience of digital transformation, this paper proposes a digital fault knowledge model construction process and method for nuclear power plant components, which is of great significance for standardizing and guiding domestic nuclear power plant knowledge models.

Optimal operation strategy for renewable power plants based on 5G base stations response

Abstract The integration of large-scale new energy sources has led to a significant challenge in electricity supply and demand balancing within the power system. To address this issue, it is crucial to establish an optimization strategy of renewable power plant based on 5G base stations response. Firstly, according to the operating state of the base station, the energy storage schedulable strategy of the base station was designed. Then, through the regulation function of the base station’s reserve energy storage and the operation principle of the renewable energy power plant, the operation model of the renewable power plant considering the base station’s participation and response was established. Finally, evaluation indexes such as the absolute peak-to-valley difference, the standard deviation of daily load and the peak-valley difference rate can be used to measure system optimization results. The results show that the proposed strategy improves the source load imbalance in the power system while enhancing reliability and economy of new energy.

Integrated wind farm solutions: Harnessing clean energy for electricity, hydrogen, and freshwater production

This research explores the design, modeling, and feasibility of a multi-energy wind power plant in South Korea, aimed at producing electricity, fresh water, hydrogen, and oxygen. The main goal of the current study is to help the energy production system that uses the high potential of wind energy in areas with wind potential to increase power and efficiency and reduce harmful environmental effects for the production of hydrogen and fresh water. The system employs a PEM electrolyzer unit and reverses osmosis technology for hydrogen, oxygen, and freshwater generation. The innovation of this study lies in the integration of wind farm design with optimal electricity allocation to electrolyzers, reverse osmosis units, and the grid, maximizing efficiency and sustainability. A comprehensive case study is presented, evaluating the viability of putting the suggested strategy into practice in ten South Korean cities, with a focus on hydrogen production from wind energy. The study investigates ten scenarios for selecting the number of wind turbines, electrolyzers, and reverse osmosis devices, and sixteen scenarios for dividing wind farm coefficients to supply grid electricity, electrolyzer electricity, and reverse osmosis electricity. The optimal result indicates that 5% of wind farm electricity should be allocated to reverse osmosis units, 15% to electrolyzers, and 80% to the grid. The economic analysis indicates that among the system components, the wind farm, reverse osmosis, and PEM electrolyzer represent the highest costs. The system's performance is assessed across ten cities in South Korea, with Yeosu, Incheon, and Busan determined to be the best sites for the proposed power plant because of their strong potential to produce hydrogen using wind energy. Implementing the system in Yeosu, the optimal city, may stop 9664.326 tons of carbon dioxide from being released, generate 47374.15 MWh of electricity, and expand 46 ha of green space. Additionally, selling 9474.83 MW of electricity to the grid would meet the annual electricity needs of 929 people in Yeosu, South Korea. This study emphasizes the potential of wind power plants in South Korea to contribute to sustainable energy production and carbon dioxide reduction, highlighting their potential for a greener and more sustainable future.

Optimal strategies for virtual power plants to participate in medium- and long-term power trading in the context of contracts for difference (CFDs)

Abstract In the context of virtual power plants gradually joining the medium-and long-term power market transactions, the decision-making problem of this new subject in the transaction process has attracted wide attention. Since virtual power plants possess distributed power sources on the supply side, as well as variable loads, energy storage, and other resources on the customer side, they are able to participate in both the sale and purchase of electricity in the medium-and long-term electricity market at the same time, which leads to the need for the relevant analysis to be divided into the two cases of sale and purchase of electricity. At the same time, due to the wide application of the CFD mechanism, power transactions should also take into account the compensation adjustment brought by this mechanism in addition to the market price. To sum up, this paper constructs a static game model for the virtual power plant’s power sales and purchasing strategies in the medium-and long-term power market under the premise of the CFD mechanism. The analysis shows that the optimal trading volume is related to the CFD volume, the total volume of power supplied by the bidding, the market price, etc. The relevant conclusions will help market managers to grasp the market price. The conclusions of the analysis help market managers grasp the key transaction information and assist virtual power plants to participate in medium-and long-term power transactions in an orderly manner.

Development of optimization control system for chiller plant based on a predictive model with Multi Stack LSTM and Deep Learning Neural Network Multi Output

Net-zero emissions become necessary for every country, implementing energy efficiency is the way to achieve it. Released report by the International Energy Agency in September 2022 stated that energy efficiency and electrification are the main priorities for Indonesia in achieving NZE. Currently, more than 50 % of energy consumption in buildings is intended for cooling systems (chillers plants). Thus, energy efficiency in buildings cooling systems has great potential to help achieve NZE and support SDGs. This research is intended to find an optimization control system for chiller plant in order to reduce energy consumption of cooling system in building. The development of this optimization control system is based on predictive model with Multi Stack LSTM and Deep Learning Neural Network. This research developed four different optimization control system frameworks. Every developed framework then will be tested by carrying out simulation with Chiller Plant model. The important parameter was found by using correlation matrix. Based on the correlation matrix, it was found that the most influence parameter that affect chiller plant performance are Tcws and Twb. It leads developed Frameworks 1 become the best compared with others developed frameworks in this research, because it used Twb as a variable input in parallel with performance prediction. This developed framework has deficient error MAE, MSE, RMSE respectively 0.8079, 0.6527, 0.8079 and able to reduce energy consumption by 10.72 %.

Generation of artificial earthquake time histories and power spectral density for seismic analysis of nuclear power plants

Regulatory Guide (RG) 1.60 presents the response spectra for the seismic design of nuclear power plants. New reactor designs necessitate Modified Design Response Spectra (MDRS), extending the high-frequency range from Design Response Spectra (DRS) in RG 1.60. This paper explores the generation procedure of artificial earthquake time histories conforming to acceptable criteria outlined in SRP Section 3.7.1 for MDRS. The process involves defining MDRS, generating artificial time histories, calculating Power Spectral Density (PSD), and producing Artificial Earthquake Ground Motions (AEGMs). Modified spectra broaden the high-frequency range and increase acceleration values at specific frequencies. For AEGM generation, two Approaches are explored using P-CARES and in-house code. Generated AEGMs satisfy the criteria outlined in SRP Section 3.7.1, ensuring compatibility with target response spectra. Additionally, seismic analyses of a nuclear power plant model, both with or without a base isolator, are conducted, and the results of the structural response using the seismic ground motion produced through the two Approaches are compared. The seismic response of the nuclear power plant model based on Approach 1 is somewhat higher than that based on Approach 2. The accelerations of the structure with the base isolator are significantly reduced compared to the structure without the base isolator.

Polymeric Nanocarriers Autonomously Cross the Plant Cell Wall and Enable Protein Delivery for Stress Sensing.

Delivery of proteins in plant cells can facilitate the design of desired functions by modulation of biological processes and plant traits but is currently limited by narrow host range, tissue damage, and poor scalability. Physical barriers in plants, including cell walls and membranes, limit protein delivery to desired plant tissues. Herein, a cationic high aspect ratio polymeric nanocarriers (PNCs) platform is developed to enable efficient protein delivery to plants. The cationic nature of PNCs binds proteins through electrostatic. The ability to precisely design PNCs' size and aspect ratio allowed us to find a cutoff of ≈14nm in the cell wall, below which cationic PNCs can autonomously overcome the barrier and carry their cargo into plant cells. To exploit these findings, a reduction-oxidation sensitive green fluorescent protein (roGFP) is deployed as a stress sensor protein cargo in a model plant Nicotiana benthamiana and common crop plants, including tomato and maize. In vivo imaging of PNC-roGFP enabled optical monitoring of plant response to wounding, biotic, and heat stressors. These results show that PNCs can be precisely designed below the size exclusion limit of cell walls to overcome current limitations in protein delivery to plants and facilitate species-independent plant engineering.