Global iron and steel plant CO2 emissions and carbon-neutrality pathways.

The highly energy-intensive iron and steel industry contributed about 25% (ref. 1) of global industrial CO2 emissions in 2019 and is therefore critical for climate-change mitigation. Despite discussions of decarbonization potentials at national and global levels2-6, plant-specific mitigation potentials and technologically driven pathways remain unclear, which cumulatively determines the progress of net-zero transition of the global iron and steel sector. Here we develop a CO2 emissions inventory of 4,883 individual iron and steel plants along with their technical characteristics, including processing routes and operating details (status, age, operation-years etc.). We identify and match appropriate emission-removal or zero-emission technologies to specific possessing routes, or what we define thereafter as a techno-specific decarbonization road map for every plant. We find that 57% of global plants have 8-24 operational years, which is the retrofitting window for low-carbon technologies. Low-carbon retrofitting following the operational characteristics of plants is key for limiting warming to 2 °C, whereas advanced retrofitting may help limit warming to 1.5 °C. If each plant were retrofitted 5 years earlier than the planned retrofitting schedule, this could lead to cumulative global emissions reductions of 69.6 (±52%) gigatonnes (Gt) CO2 from 2020 to 2050, almost double that of global CO2 emissions in 2021. Our results provide a detailed picture of CO2 emission patterns associated with production processing of iron and steel plants, illustrating the decarbonization pathway to the net-zero-emissions target with the efforts from each plant.

Dynamic Transformation of Nano-MoS2 in a Soil-Plant System Empowers Its Multifunctionality on Soybean Growth.

Molybdenum disulfide (nano-MoS2) nanomaterials have shown great potential for biomedical and catalytic applications due to their unique enzyme-mimicking properties. However, their potential agricultural applications have been largely unexplored. A key factor prior to the application of nano-MoS2 in agriculture is understanding its behavior in a complex soil-plant system, particularly in terms of its transformation. Here, we investigate the distribution and transformation of two types of nano-MoS2 (MoS2 nanoparticles and MoS2 nanosheets) in a soil-soybean system through a combination of synchrotron radiation-based X-ray absorption near-edge spectroscopy (XANES) and single-particle inductively coupled plasma mass spectrometry (SP-ICP-MS). We found that MoS2 nanoparticles (NPs) transform dynamically in soil and plant tissues, releasing molybdenum (Mo) and sulfur (S) that can be incorporated gradually into the key enzymes involved in nitrogen metabolism and the antioxidant system, while the rest remain intact and act as nanozymes. Notably, there is 247.9 mg/kg of organic Mo in the nodule, while there is only 49.9 mg/kg of MoS2 NPs. This study demonstrates that it is the transformation that leads to the multifunctionality of MoS2, which can improve the biological nitrogen fixation (BNF) and growth. Therefore, MoS2 NPs enable a 30% increase in yield compared to the traditional molybdenum fertilizer (Na2MoO4). Excessive transformation of MoS2 nanosheets (NS) leads to the overaccumulation of Mo and sulfate in the plant, which damages the nodule function and yield. The study highlights the importance of understanding the transformation of nanomaterials for agricultural applications in future studies.

ChatGPT and Google Assistant as a Source of Patient Education for Patients With Amblyopia: Content Analysis.

BACKGROUND: We queried ChatGPT (OpenAI) and Google Assistant about amblyopia and compared their answers with the keywords found on the American Association for Pediatric Ophthalmology and Strabismus (AAPOS) website, specifically the section on amblyopia. Out of the 26 keywords chosen from the website, ChatGPT included 11 (42%) in its responses, while Google included 8 (31%). OBJECTIVE: Our study investigated the adherence of ChatGPT-3.5 and Google Assistant to the guidelines of the AAPOS for patient education on amblyopia. METHODS: ChatGPT-3.5 was used. The four questions taken from the AAPOS website, specifically its glossary section for amblyopia, are as follows: (1) What is amblyopia? (2) What causes amblyopia? (3) How is amblyopia treated? (4) What happens if amblyopia is untreated? Approved and selected by ophthalmologists (GW and DL), the keywords from AAPOS were words or phrases that deemed significant for the education of patients with amblyopia. The "Flesch-Kincaid Grade Level" formula, approved by the US Department of Education, was used to evaluate the reading comprehension level for the responses from ChatGPT, Google Assistant, and AAPOS. RESULTS: In their responses, ChatGPT did not mention the term "ophthalmologist," whereas Google Assistant and AAPOS both mentioned the term once and twice, respectively. ChatGPT did, however, use the term "eye doctors" once. According to the Flesch-Kincaid test, the average reading level of AAPOS was 11.4 (SD 2.1; the lowest level) while that of Google was 13.1 (SD 4.8; the highest required reading level), also showing the greatest variation in grade level in its responses. ChatGPT's answers, on average, scored 12.4 (SD 1.1) grade level. They were all similar in terms of difficulty level in reading. For the keywords, out of the 4 responses, ChatGPT used 42% (11/26) of the keywords, whereas Google Assistant used 31% (8/26). CONCLUSIONS: ChatGPT trains on texts and phrases and generates new sentences, while Google Assistant automatically copies website links. As ophthalmologists, we should consider including "see an ophthalmologist" on our websites and journals. While ChatGPT is here to stay, we, as physicians, need to monitor its answers.

The fate and impact of Co3O4 nanoparticles in the soil environment: Observing the dose effect of nanoparticles on soybeans.

The widespread presence and distribution of metal-based nanoparticles (NPs) in soil is threatening crop growth and food security. However, little is known about the fate of Co3O4 NPs in the soil-soybean system and their phytotoxicity. The study demonstrated the effects of Co3O4 NPs on soybean growth and yield in soil after 60 days and 140 days, and compared them with the phytotoxic effects of Co2+. The results showed that Co3O4 NPs (10-500 mg/kg) had no significant toxic effect on soybeans. Soil available Co content was significantly increased under 500 mg/kg Co3O4 NPs treatment. Compared with Co2+, Co3O4 NPs mainly accumulated in roots and had limited transport to the shoots, which was related to the particle size, surface charge and chemical stability of Co3O4 NPs. The significant accumulation of Co3O4 NPs in roots further led to a significant decrease in root antioxidant enzyme activity and changes in functional gene expression. Co3O4 NPs reduced soybean yield after 140 days, but interestingly, at specific doses, it increased grain nutrients (Fe content increased by 17.38% at 100 mg/kg, soluble protein and vitamin E increased by 14.34% and 16.81% at 10 mg/kg). Target hazard quotient (THQ) assessment results showed that consuming soybean seeds exposed to Co3O4 NPs (≥100 mg/kg) and Co2+ (≥10 mg/kg) would pose potential health risks. Generally, Co3O4 NPs could exist stably in the environment and had lower environmental risks than Co2+. These results help to better understand the environmental behavior and plant effect mechanisms of Co3O4 NPs in soil-plant systems.

Lead-Free Relaxor Ferroelectric Ceramics with Ultrahigh Energy Storage Densities via Polymorphic Polar Nanoregions Design.

One of the long-standing challenges of current lead-free energy storage ceramics for capacitors is how to improve their comprehensive energy storage properties effectively, that is, to achieve a synergistic improvement in the breakdown strength (Eb ) and the difference between maximum polarization (Pmax ) and remnant polarization (Pr ), making them comparable to those of lead-based capacitor materials. Here, a polymorphic polar nanoregions (PNRs) structural design by first introducing 0.06 mol BaTiO3 into Bi0.5 Na0.5 TiO3 is proposed to construct the morphotropic phase boundary with coexisting structures of micrometer-size domains and polymorphic nanodomains, enhance the electric field-induced polarization response (increase Pmax ). Then Sr(Al0.5 Ta0.5 )O3 (SAT)-doped 0.94 Bi0.5 Na0.5 TiO3 -0.06BaTiO3 (BNBT) energy storage ceramics with polymorphic PNRs structures are synthesized following the guidance of phase-field simulation and rational composition design (decrease Pr ). Finally, a large recoverable energy density (Wrec ) of 8.33 J cm-3 and a high energy efficiency (η) of 90.8% under 555 kV cm-1 are obtained in the 0.85BNBT-0.15SAT ceramic prepared by repeated rolling process method (enhance Eb ), superior to most practical lead-free competitors increased consideration of the stability of temperature (a variation <±6.2%) and frequency (Wrec > 5.0  cm-3 , η > 90%) at 400 kV cm-1 . This strategy provides a new conception for the design of other-based multifunctional energy storage dielectrics.

MtESN2 is a subgroup II sulphate transporter required for symbiotic nitrogen fixation and prevention of nodule early senescence in Medicago truncatula.

Adequate distribution of mineral sulphur (S) nutrition to nodules mediated by sulphate transporters is crucial for nitrogen fixation in symbiosis establishment process. However, the molecular mechanisms underlying this process remain largely unknown. In this study, we characterized the function of Early Senescent Nodule 2 (MtESN2), a gene crucial to nitrogen fixation in Medicago truncatula. Mutations in MtESN2 resulted in severe developmental and functional defects including dwarf shoots, early senescent nodules, and lower nitrogenase activity under symbiotic conditions compared to wild-type plants. MtESN2 encodes an M. truncatula sulphate transporter that is expressed only in roots and nodules, with the highest expression levels in the transition zone and nitrogen-fixing zone of nodules. MtESN2 exhibited sulphate transport activity when expressed in yeast. Immunolocalization analysis showed that MtESN2-yellow fluorescent protein fusion protein was localized to the plasma membranes of both uninfected and infected cells of nodules, where it might transport sulphate into both rhizobia-infected and uninfected cells within the nodules. Our results reveal an unreported sulphate transporter that contributes to effective symbiosis and prevents nodule early senescence in M. truncatula.

Nickel Oxide Nanoparticles Improve Soybean Yield and Enhance Nitrogen Assimilation.

Nickel (Ni) is a trace element beneficial for plant growth and development and could improve crop yield by stimulating urea decomposition and nitrogen-fixing enzyme activity. A full life cycle study was conducted to compare the long-term effects of soil-applied NiO nanoparticles (n-NiO), NiO bulk (b-NiO), and NiSO4 at 10-200 mg kg-1 on plant growth and nutritional content of soybean. n-NiO at 50 mg kg-1 significantly promoted the seed yield by 39%. Only 50 mg kg-1 n-NiO promoted total fatty acid content and starch content by 28 and 19%, respectively. The increased yield and nutrition could be attributed to the regulatory effects of n-NiO, including photosynthesis, mineral homeostasis, phytohormone, and nitrogen metabolism. Furthermore, n-NiO maintained a Ni2+ supply for more extended periods than NiSO4, reducing potential phytotoxicity concerns. Single-particle inductively coupled plasma mass spectrometry (sp-ICP-MS) for the first time confirmed that the majority of the Ni in seeds is in ionic form, with only 28-34% as n-NiO. These findings deepen our understanding of the potential of nanoscale and non-nanoscale Ni to accumulate and translocate in soybean, as well as the long-term fate of these materials in agricultural soils as a strategy for nanoenabled agriculture.

The role of discoid domain receptor 1 on renal tubular epithelial pyroptosis in diabetic nephropathy.

Pyroptosis, a form of cell death associated with inflammation, is known to be involved in diabetic nephropathy (DN), and discoid domain receptor 1 (DDR1), an inflammatory regulatory protein, is reported to be associated with diabetes. However, the mechanism underlying DDR1 regulation and pyroptosis in DN remains unknown. We aimed to investigate the effect of DDR1 on renal tubular epithelial cell pyroptosis and the mechanism underlying DN. In this study, we used high glucose (HG)-treated HK-2 cells and rats with a single intraperitoneal injection of streptozotocin as DN models. Subsequently, the expression of pyroptosis-related proteins (cleaved caspase-1, GSDMD-N, Interleukin-1ß [IL-1ß], and interleukin-18 [IL-18]), DDR1, phosphorylated NF-κB (p-NF-κB), and NLR family pyrin domain-containing 3 (NLRP3) inflammasomes were determined through Western blotting. IL-1ß and IL-18 levels were determined using ELISA. The rate of pyroptosis was assessed by propidium iodide (PI) staining. The results revealed upregulated expression of pyroptosis-related proteins and increased concentration of IL-1ß and IL-18, accompanied by DDR1, p-NF-κB, and NLRP3 upregulation in DN rat kidney tissues and HG-treated HK-2 cells. Moreover, DDR1 knockdown in the background of HG treatment resulted in inhibited expression of pyroptosis-related proteins and attenuation of IL-1ß and IL-18 production and PI-positive cell frequency via the NF-κB/NLRP3 pathway in HK-2 cells. However, NLRP3 overexpression reversed the effect of DDR1 knockdown on pyroptosis. In conclusion, we demonstrated that DDR1 may be associated with pyroptosis, and DDR1 knockdown inhibited HG-induced renal tubular epithelial cell pyroptosis. The NF-κB/NLRP3 pathway is probably involved in the underlying mechanism of these findings.

Highly Responsive and Ultrasensitive Non-Enzymatic Electrochemical Glucose Sensor Based on Au Foam.

Glucose concentration is an important physiological index, therefore methods for sensitive detection of glucose are important. In this study, Au foam was prepared by electrodeposition with a dynamic gas template on an Au nanoparticle/Si substrate. The Au foam showed ultrasensitivity, high selectivity, and long-term stability in the quantitative detection of glucose. The foam was used as an electrode, and the amperometric response indicated excellent catalytic activity in glucose oxidation, with a linear response across the concentration range 0.5 µM to 12 mM, and a limit of detection of 0.14 µM. High selectivity for interfering molecules at six times the normal level and long-term stability for 30 days were obtained. The results for electrochemical detection with Au foam of glucose in human serum were consistent with those obtained with a sensor based on surface-enhanced Raman spectroscopy and a commercial sensor. This proves that this method can be used with real samples. These results show that Au foam has great potential for use as a non-enzymatic glucose sensor.

Patients with floaters: Answers from virtual assistants and large language models.

Objectives: "Floaters," a common complaint among patients of all ages, was used as a query term because it affects 30% of all people searching for eye care. The American Academy of Ophthalmology website's "floaters" section was used as a source for questions and answers (www.aao.org). Floaters is a visual obstruction that moves with the movement of the eye. They can be associated with retinal detachment, which can lead to vision loss. With the advent of large language model (LLM) chatbots ChatGPT, Bard versus virtual assistants (VA), Google Assistant, and Alexa, we analyzed their responses to "floaters." Methods: Using AAO.org, "Public & Patients," and its related subsection, "EyeHealth A-Z": Floaters and Flashes link, we asked four questions: (1) What are floaters? (2) What are flashes? (3) Flashes and Migraines? (4) Floaters and Flashes Treatment? to ChatGPT, Bard, Google Assistant, and Alexa. The American Academy of Ophthalmology (AAO) keywords were identified if they were highlighted. The "Flesch-Kincaid Grade Level" formula approved by the U.S. Department of Education, was used to evaluate the reading comprehension level for the responses. Results: Of the chatbots and virtual assistants, Google Assistant is the only one that uses the term "ophthalmologist." There is no mention of the urgency or emergency nature of floaters. AAO.org shows a lower reading level vs the LLMs and VA (p = .11). The reading comprehension levels of ChatGPT, Bard, Google Assistant, and Alexa are higher (12.3, 9.7, 13.1, 8.1 grade) vs the AAO.org (7.3 grade). There is a higher word count for LLMs vs VA (p < .0286). Conclusion: Currently, ChatGPT, Bard, Google Assistant, and Alexa are similar. Factual information is present but all miss the urgency of the diagnosis of a retinal detachment. Translational relevance: Both the LLM and virtual assistants are free and our patients will use them to obtain "floaters" information. There may be errors of omission with ChatGPT and a lack of urgency to seek a physician's care.

Insights into the effect of manganese-based nanomaterials on the distribution trait and nutrition of radish (Raphanus sativus L.).

Manganese (Mn) is one of the essential elements for plant growth and is involved in the process of photosynthesis and seed germination. Herein, we applied two Mn-based nanoparticles, MnO2 and Mn3O4, to the soil to investigate their effects on radish growth, antioxidant system, and nutrients. The radish plant height after treatment with 10 mg/kg of MnO2 and Mn3O4 NPs were increased, compare to the control. In radish's shoot, MnO2 NPs at high concentrations (100 mg/kg) increased MDA activity by 58 % compared to the control group, while exposure to Mn3O4 NPs at the same concentration decreased MDA activity by 14 %. The nutrient content of radishes, such as soluble sugar and vitamin C, was improved. Moreover, single particle inductively coupled plasma mass spectrometry (SP ICP-MS) was used to understand the patterns of migration of Mn-based NPs in radish and subsequent impact on nutrients. We found that Mn-based NPs accumulated mainly in the roots of radish. Interestingly, the accumulation characteristics of MnO2 NPs and Mn3O4 NPs were different. MnO2 NPs accumulated more in radish leaves than in fruits, while the accumulation of Mn3O4 NPs gradually decreased from roots to leaves. Finally, we determined the mineral element content of the leaves, fruits, and roots of radish, and found that the uptake of main metallic mineral elements (e.g. Cu, Fe, Mg, Zn, Na, K) was inhibited by the application of Mn-based NPs. These findings underscore the importance of considering species and multifaceted impacts of Mn-based NPs as nanofertilizers for their wide application in agriculture.

Harnessing synergy: Integrating agricultural waste and nanomaterials for enhanced sustainability.

This paper aims to explore the cooperative use of agricultural waste and nanomaterials to improve environmental sustainability. The introduction highlights global environmental challenges and the objectives of integrating the two are highlighted. Valorization of agricultural waste is considered to reduce waste generation, while nanomaterials act as conversion catalysts that help to increase the efficiency of waste conversion and environmental remediation. In addition, synergistic approaches are discussed, including the combination of agricultural waste and nanomaterials, as well as the concept of enhanced resource management. The paper also presents case studies that demonstrate the success of such synergistic applications in pollution control and environmental remediation. Despite the challenges and risks, this approach can provide new ways to create more sustainable and resilient environments through the integration of resources, interdisciplinary cooperation and policy support.

The combination of nanotechnology and potassium: applications in agriculture.

Potassium fertilizer is indispensable for ensuring crop production, which in turn supports global food supply and safe farming practices. Potassium resources are primarily located in the Northern Hemisphere, leading to a current shortage of affordable potash and severe soil deficiencies in certain regions of the Southern Hemisphere. There is a shift away from mined salts in favor of locally available potassium resources. Utilizing potassium-rich silicates, for instance, could be a viable option to address this situation. The imperative of enhancing crop productivity and quality necessitates either increasing potassium availability or utilizing potassium more efficiently. Geneticists may find the development of plants that use potassium more effectively to be a valuable pursuit. Nanomaterials are increasingly becoming part of people's professional lives as a novel material category. This technology is gradually finding applications in agriculture to boost crop yields while reducing environmental pollution. This paper reviews the applications of common potassium-containing materials, explores the effects and mechanisms of nano-fertilizers on plants, and offers insights into future applications of nano-potassium fertilizers in agriculture. All in all, the application of nanotechnology in the production and utilization of potassium fertilizers is both necessary and effective. However, there are still many gaps in the current field of nano-potassium fertilizer application that require further research. It is hoped that this review can serve as a valuable reference for researchers working in this field.

Investigation of the effects and mechanisms of manganese-based NMs on rice growth.

Manganese-based (Mn-based) nanomaterials (NMs) have great potential as alternatives to conventional Mn fertilizers. Yet, its environmental risks and effects on plant growth are not completely well understood. This study investigated the physiological effects of manganese dioxide (MnO2) and manganese tetroxide (Mn3O4) NMs on inter-root exposure (0-500 mg/L) of hydroponically grown rice. The results showed that on inter-root exposure, 50 mg/L Mn-based NMs promoted the uptake of mineral elements and enhanced the enzymatic activities of antioxidant systems (CAT and SOD) in rice, whereas 500 mg/L Mn3O4 NMs disrupted the mineral element homeostasis and led to phytotoxicity. The promotion effect of MnO2 NMs was better, firstly because MnO2 NMs treatment had lower Mn content in the plant than Mn3O4 NMs. In addition, MnO2 NMs are more transported and absorbed in the plant in ionic form, while Mn3O4 NMs exist in granular form. MnO2 NMs and Mn3O4 NMs both can be used as nano-fertilizers to improve the growth of rice by inter-root application, but the doses should be carefully selected.

Multiplexed CRISPR gene editing in primary human islet cells with Cas9 ribonucleoprotein.

Successful genome editing in primary human islets could reveal features of the genetic regulatory landscape underlying ß cell function and diabetes risk. Here, we describe a CRISPR-based strategy to interrogate functions of predicted regulatory DNA elements using electroporation of a complex of Cas9 ribonucleoprotein (Cas9 RNP) and guide RNAs into primary human islet cells. We successfully targeted coding regions including the PDX1 exon 1, and non-coding DNA linked to diabetes susceptibility. CRISPR-Cas9 RNP approaches revealed genetic targets of regulation by DNA elements containing candidate diabetes risk SNPs, including an in vivo enhancer of the MPHOSPH9 gene. CRISPR-Cas9 RNP multiplexed targeting of two cis-regulatory elements linked to diabetes risk in PCSK1, which encodes an endoprotease crucial for Insulin processing, also demonstrated efficient simultaneous editing of PCSK1 regulatory elements, resulting in impaired ß cell PCSK1 regulation and Insulin secretion. Multiplex CRISPR-Cas9 RNP provides powerful approaches to investigate and elucidate human islet cell gene regulation in health and diabetes.

RFX6 Maintains Gene Expression and Function of Adult Human Islet α-Cells.

Mutations in the gene encoding the transcription factor regulatory factor X-box binding 6 (RFX6) are associated with human diabetes. Within pancreatic islets, RFX6 expression is most abundant in islet α-cells, and α-cell RFX6 expression is altered in diabetes. However, the roles of RFX6 in regulating gene expression, glucagon output, and other crucial human adult α-cell functions are not yet understood. We developed a method for selective genetic targeting of human α-cells and assessed RFX6-dependent α-cell function. RFX6 suppression with RNA interference led to impaired α-cell exocytosis and dysregulated glucagon secretion in vitro and in vivo. By contrast, these phenotypes were not observed with RFX6 suppression across all islet cells. Transcriptomics in α-cells revealed RFX6-dependent expression of genes governing nutrient sensing, hormone processing, and secretion, with some of these exclusively expressed in human α-cells. Mapping of RFX6 DNA-binding sites in primary human islet cells identified a subset of direct RFX6 target genes. Together, these data unveil RFX6-dependent genetic targets and mechanisms crucial for regulating adult human α-cell function.

Metal-Organic Frameworks for Sustainable Crop Disease Management: Current Applications, Mechanistic Insights, and Future Challenges.

Efficient management of crop diseases and yield enhancement are essential for addressing the increasing food demands due to global population growth. Metal-organic frameworks (MOFs), which have rapidly evolved throughout the 21st century, are notable for their vast surface area, porosity, and adaptability, establishing them as highly effective vehicles for controlled drug delivery. This review methodically categorizes common MOFs employed in crop disease management and details their effectiveness against various pathogens. Additionally, by critically evaluating existing research, it outlines strategic approaches for the design of drug-delivery MOFs and explains the mechanisms through which MOFs enhance disease resistance. Finally, this paper identifies the current challenges in MOF research for crop disease management and suggests directions for future research. Through this in-depth review, the paper seeks to enrich the understanding of MOFs applications in crop disease management and offers valuable insights for researchers and practitioners.

A learnable sampling method for scalable graph neural networks.

With the development of graph neural networks, how to handle large-scale graph data has become an increasingly important topic. Currently, most graph neural network models which can be extended to large-scale graphs are based on random sampling methods. However, the sampling process in these models is detached from the forward propagation of neural networks. Moreover, quite a few works design sampling based on statistical estimation methods for graph convolutional networks and the weights of message passing in GCNs nodes are fixed, making these sampling methods not scalable to message passing networks with variable weights, such as graph attention networks. Noting the end-to-end learning capability of neural networks, we propose a learnable sampling method. It solves the problem that random sampling operations cannot calculate gradients and samples nodes with an unfixed probability. In this way, the sampling process is dynamically combined with the forward propagation process of the features, allowing for better training of the networks. And it can be generalized to all message passing models. In addition, we apply the learnable sampling method to GNNs and propose two models. Our method can be flexibly combined with different graph neural network models and achieves excellent accuracy on benchmark datasets with large graphs. Meanwhile, loss function converges to smaller values at a faster rate during training than past methods.

AgNPs-Triggered Seed Metabolic and Transcriptional Reprogramming Enhanced Rice Salt Tolerance and Blast Resistance.

Seeds are facing harsher environments due to the changing climate. Improving seeds' stress resilience is critical to reduce yield loss. Here, we propose that using ROS-generating nanoparticles (NPs) to prestimulate seeds would enhance the stress resilience of seeds and seedlings through triggering stress/immune responses. We examined this hypothesis by exposing AgNPs-primed rice (Oryza sativa L.) seeds under salt conditions (NaCl). The results showed that primed seeds exhibit accelerated germination speed, increased seedling vigor (from 22.5 to 47.6), biomass (11%), and root length (83%) compared to seeds with hydropriming treatment. Multiomics (metabolomics and transcriptomics) analyses reveal that AgNPs-priming triggered metabolic and transcriptional reprogramming in rice seeds. Signaling metabolites, such as salicylic acid, niacinamide, and glycerol-3-phosphate, dramatically increased upon AgNPs-priming. KEGG pathway analysis reveals that AgNPs-priming activated stress signaling and defense related pathways, such as plant hormone signal transduction, glutathione metabolism, flavone and flavonol biosynthesis, MAPK signaling pathway, and plant-pathogen interaction. These metabolic and transcriptional changes indicate that AgNPs-priming triggered stress/immune responses. More importantly, this "stress memory" can last weeks, providing protection to rice seedlings against salt stress and rice blast fungus (Magnaporthe oryzae). Overall, we show that prestimulated seeds with ROS-generating AgNPs not only enable faster and better germination under stress conditions, but also increase seedling resistance to biotic and abiotic stresses. This simple nanobiostimulant-based strategy may contribute to sustainable agriculture by maintaining agricultural production and reducing the use of pesticides.

Real-Time Classification of Motor Imagery Using Dynamic Window-Level Granger Causality Analysis of fMRI Data.

This article presents a method for extracting neural signal features to identify the imagination of left- and right-hand grasping movements. A functional magnetic resonance imaging (fMRI) experiment is employed to identify four brain regions with significant activations during motor imagery (MI) and the effective connections between these regions of interest (ROIs) were calculated using Dynamic Window-level Granger Causality (DWGC). Then, a real-time fMRI (rt-fMRI) classification system for left- and right-hand MI is developed using the Open-NFT platform. We conducted data acquisition and processing on three subjects, and all of whom were recruited from a local college. As a result, the maximum accuracy of using Support Vector Machine (SVM) classifier on real-time three-class classification (rest, left hand, and right hand) with effective connections is 69.3%. And it is 3% higher than that of traditional multivoxel pattern classification analysis on average. Moreover, it significantly improves classification accuracy during the initial stage of MI tasks while reducing the latency effects in real-time decoding. The study suggests that the effective connections obtained through the DWGC method serve as valuable features for real-time decoding of MI using fMRI. Moreover, they exhibit higher sensitivity to changes in brain states. This research offers theoretical support and technical guidance for extracting neural signal features in the context of fMRI-based studies.