New isoforms and assembly of glutamine synthetase in the leaf of wheat (Triticum aestivum L.).

Glutamine synthetase (GS; EC 6.3.1.2) plays a crucial role in the assimilation and re-assimilation of ammonia derived from a wide variety of metabolic processes during plant growth and development. Here, three developmentally regulated isoforms of GS holoenzyme in the leaf of wheat (Triticum aestivum L.) seedlings are described using native-PAGE with a transferase activity assay. The isoforms showed different mobilities in gels, with GSII>GSIII>GSI. The cytosolic GSI was composed of three subunits, GS1, GSr1, and GSr2, with the same molecular weight (39.2kDa), but different pI values. GSI appeared at leaf emergence and was active throughout the leaf lifespan. GSII and GSIII, both located in the chloroplast, were each composed of a single 42.1kDa subunit with different pI values. GSII was active mainly in green leaves, while GSIII showed brief but higher activity in green leaves grown under field conditions. LC-MS/MS experiments revealed that GSII and GSIII have the same amino acid sequence, but GSII has more modification sites. With a modified blue native electrophoresis (BNE) technique and in-gel catalytic activity analysis, only two GS isoforms were observed: one cytosolic and one chloroplastic. Mass calibrations on BNE gels showed that the cytosolic GS1 holoenzyme was ~490kDa and likely a dodecamer, and the chloroplastic GS2 holoenzyme was ~240kDa and likely a hexamer. Our experimental data suggest that the activity of GS isoforms in wheat is regulated by subcellular localization, assembly, and modification to achieve their roles during plant development

Evaluation and Design of Colored Silicon Nanoparticle Systems Using a Bidirectional Deep Neural Network

Silicon nanoparticles (SiNPs) with lowest-order Mie resonance produce non-iridescent and non-fading vivid structural colors in the visible range. However, the strong wavelength dependence of the radiation pattern and dielectric function makes it very difficult to design nanoparticle systems with the desired colors. Most existing studies focus on monodisperse nanoparticle systems, which are unsuitable for practical applications. This study combined the Lorentz–Mie theory, Monte Carlo, and deep neural networks to evaluate and design colored SiNP systems. The effects of the host medium and particle size distribution on the optical and color properties of the SiNP systems were investigated. A bidirectional deep neural network achieved accurate prediction and inverse design of structural colors. The results demonstrated that the particle size distribution flattened the Mie resonance peak and influenced the reflectance and brightness of the SiNP system. The SiNPs generated vivid colors in all three of the host media. Meanwhile, our proposed neural network model achieved a near-perfect prediction of colors with high accuracy of the designed geometric parameters. This work accurately and efficiently evaluates and designs the optical and color properties of SiNP systems, thus accelerating the design process and contributing to the practical production design of color inks, decoration, and printing

Progress on Self-Powered Wearable and Implantable Systems Driven by Nanogenerators

With the rapid development of the internet of things (IoT), sustainable self-powered wireless sensory systems and diverse wearable and implantable electronic devices have surged recently. Under such an opportunity, nanogenerators, which can convert continuous mechanical energy into usable electricity, have been regarded as one of the critical technologies for self-powered systems, based on the high sensitivity, flexibility, and biocompatibility of piezoelectric nanogenerators (PENGs) and triboelectric nanogenerators (TENGs). In this review, we have thoroughly analyzed the materials and structures of wearable and implantable PENGs and TENGs, aiming to make clear how to tailor a self-power system into specific applications. The advantages in TENG and PENG are taken to effectuate wearable and implantable human-oriented applications, such as self-charging power packages, physiological and kinematic monitoring, in vivo and in vitro healing, and electrical stimulation. This review comprehensively elucidates the recent advances and future outlook regarding the human body’s self-powered systems

Quantitative Evaluation of the Phase Function Effects on Light Scattering and Radiative Transfer in Dispersed Systems

The light scattering properties of particles play important roles in radiative transfer in many dispersed systems, such as turbid atmosphere, ocean water, nanofluids, composite coatings and so on. As one of the scattering property parameters, the scattering phase functions of particles are strongly dependent on the particle size, size distribution, and morphology, as well as on the complex refractive indices of the particles and surrounding media. For the sake of simplicity, the empirical phase function models are widely used in many practical applications. In this work, we focus on the radiative transfer problem in dispersed systems composed of spherical particles, and give quantitative analyses of the impact of scattering phase functions on the radiative transfer process. We fit the scattering phase functions of four different types of practical dispersed systems using four previously proposed empirical phase function models, including the Henyey–Greenstein (HG) model, Cornette Shanks (CS) model, Reynold and McCormick (RM) model and two-term Reynolds–McCormick (TTRM) model. By comparing the radiative transfer characteristics (i.e., hemispherical reflectance, hemispherical transmittance and total absorptance) of dispersed layers calculated using the Monte Carlo method, the relative errors caused by using the empirical phase functions are systematically investigated. The results demonstrate that the HG, CS and RM models cause obvious errors in the calculation of hemispherical reflectance in many cases. Meanwhile, the induced errors show no obvious regularity, but are related to the particle size and layer optical thickness. Due to the good fitting effect in both forward and backward directions, the TTRM model provides significantly higher performances in fitting the phase functions of all considered cases than the widely used single-term parametrizations. Moreover, for different particle sizes and layer optical thicknesses, the induced errors of the TTRM model in radiative transfer characteristics are very small, especially for the case of polydisperse particles. Our results can be used to guide the design, analysis and optimization of dispersed systems in practical optics and photonics applications

Prediction and Inverse Design of Structural Colors of Nanoparticle Systems via Deep Neural Network

Noniridescent and nonfading structural colors generated from metallic and dielectric nanoparticles with extraordinary optical properties hold great promise in applications such as image display, color printing, and information security. Yet, due to the strong wavelength dependence of optical constants and the radiation pattern, it is difficult and time-consuming to design nanoparticles with the desired hue, saturation, and brightness. Herein, we combined the Monte Carlo and Mie scattering simulations and a bidirectional neural network (BNN) to improve the design of gold nanoparticles’ structural colors. The optical simulations provided a dataset including color properties and geometric parameters of gold nanoparticle systems, while the BNN was proposed to accurately predict the structural colors of gold nanoparticle systems and inversely design the geometric parameters for the desired colors. Taking the human chromatic discrimination ability as a criterion, our proposed approach achieved a high accuracy of 99.83% on the predicted colors and 98.5% on the designed geometric parameters. This work provides a general method to accurately and efficiently design the structural colors of nanoparticle systems, which can be exploited in a variety of applications and contribute to the development of advanced optical materials

Facile Synthesis of 3D Amino-Functional Graphene-Sponge Composites Decorated by Graphene Nanodots with Enhanced Removal of Indoor Formaldehyde

Amino-functional graphene-sponge composites decorated by graphene nanodots (G-GND/S) were synthesized. The preparation technology contributes to prevent the loss of nano-materials and reduce the adding amount of graphene. G-GND/S was used as adsorbents to remove formaldehyde, and then their performances for formaldehyde adsorption were evaluated by dynamic adsorption experiment. The adsorption properties of three different materials: sponge, graphene-sponge, and G-GND/S, the breakthrough time and adsorption capacity had been compared, the results showed G-GND/S had better formaldehyde adsorption properties with longer breakthrough time (~2137 min/g) and adsorption ability of formaldehyde (22.8 mg/g). Large amounts of amine groups were the most important factor for the strength enhancement of the adsorption efficiency

Protein Kinase RhCIPK6 Promotes Petal Senescence in Response to Ethylene in Rose (Rosa Hybrida)

Cultivated roses have the largest global market share among ornamental crops. Postharvest release of ethylene is the main cause of accelerated senescence and decline in rose flower quality. To understand the molecular mechanism of ethylene-induced rose petal senescence, we analyzed the transcriptome of rose petals during natural senescence as well as with ethylene treatment. A large number of differentially expressed genes (DEGs) were observed between developmental senescence and the ethylene-induced process. We identified 1207 upregulated genes in the ethylene-induced senescence process, including 82 transcription factors and 48 protein kinases. Gene Ontology enrichment analysis showed that ethylene-induced senescence was closely related to stress, dehydration, and redox reactions. We identified a calcineurin B-like protein (CBL) interacting protein kinase (CIPK) family gene in Rosa hybrida, RhCIPK6, that was regulated by age and ethylene induction. Reducing RhCIPK6 expression through virus-induced gene silencing significantly delayed petal senescence, indicating that RhCIPK6 mediates petal senescence. In the RhCIPK6-silenced petals, several senescence associated genes (SAGs) and transcription factor genes were downregulated compared with controls. We also determined that RhCIPK6 directly binds calcineurin B-like protein 3 (RhCBL3). Our work thus offers new insights into the function of CIPKs in petal senescence and provides a genetic resource for extending rose vase life

Unraveling the molecular interplay of ferroptosis and immune regulation in stroke pathogenesis: A comprehensive bioinformatics analysis

Neurological disorders, particularly stroke, pose significant public health challenges, prompting a comprehensive investigation into the intricate interplay between ferroptosis and immune responses. This study aims to uncover the molecular mechanisms of stroke, emphasizing the connection between ferroptosis and immune regulation. Objectives include identifying differentially expressed genes in stroke patients, assessing immune cell subtype activation, employing advanced predictive modeling to pinpoint key candidate genes such as STMN1 and ATG16L1, exploring associations with immune cell subtypes, and revealing critical pathways, such as matrix degradation and inflammatory responses, activated in stroke through Gene Set Variation Analysis (GSVA). A comprehensive approach was adopted, involving differential gene expression analysis, functional enrichment analysis, weighted gene co-expression network analysis, Lasso regularization, random forest models, and the CIBERSORT (https://cibersortx.stanford.edu) algorithm, to assess immune cell subtypes. The study pinpointed genes with significant expression differences in stroke patients, highlighting the activation of Th17 cells and the NF-κ B signaling pathway. Key candidate genes, including STMN1 and ATG16L1, were identified using advanced predictive modeling. The relative abundance of immune cell subtypes, particularly natural killer cells (NK cells) and T cell subgroups, was associated with stroke through CIBERSORT. GSVA uncovered the activation of critical biological pathways such as matrix degradation and inflammatory responses. The analysis pinpointed STMN1 and ATG16L1 as robust predictors, emphasizing their potential as therapeutic targets. Th17 cells and the NF-κ B signaling pathway emerged as pivotal contributors to stroke pathogenesis. Notably, NK cells and specific T cell subgroups demonstrated significant associations with stroke. GSVA further illuminated the activation of key pathways, providing deeper insights into the biological processes underlying stroke. This study sheds light on crucial genes and pathways implicated in stroke, emphasizing the roles of ferroptosis and immune cell subtypes. The identified genes and pathways offer promising avenues for targeted therapeutic interventions in stroke, with a broader implication for advancing neurological disorder treatments through innovative perspectives on ferroptosis and immune regulation

New isoforms and assembly of glutamine synthetase in the leaf of wheat ( Triticum aestivum

Glutamine synthetase (GS; EC 6.3.1.2) plays a crucial role in the assimilation and re-assimilation of ammonia derived from a wide variety of metabolic processes during plant growth and development. Here, three developmentally regulated isoforms of GS holoenzyme in the leaf of wheat (Triticum aestivum L.) seedlings are described using native-PAGE with a transferase activity assay. The isoforms showed different mobilities in gels, with GS(II)>GS(III)>GS(I). The cytosolic GS(I) was composed of three subunits, GS1, GSr1, and GSr2, with the same molecular weight (39.2kDa), but different pI values. GS(I) appeared at leaf emergence and was active throughout the leaf lifespan. GS(II) and GS(III), both located in the chloroplast, were each composed of a single 42.1kDa subunit with different pI values. GS(II) was active mainly in green leaves, while GS(III) showed brief but higher activity in green leaves grown under field conditions. LC-MS/MS experiments revealed that GS(II) and GS(III) have the same amino acid sequence, but GS(II) has more modification sites. With a modified blue native electrophoresis (BNE) technique and in-gel catalytic activity analysis, only two GS isoforms were observed: one cytosolic and one chloroplastic. Mass calibrations on BNE gels showed that the cytosolic GS1 holoenzyme was ~490kDa and likely a dodecamer, and the chloroplastic GS2 holoenzyme was ~240kDa and likely a hexamer. Our experimental data suggest that the activity of GS isoforms in wheat is regulated by subcellular localization, assembly, and modification to achieve their roles during plant development

Theoretical Insight into the Mechanism of Cu(I)-Catalyzed [2 + 2 + 1] Cycloaddition to β‑Pyrrolinones: Azaheterocycle Formation and Assisted Dehydrogenation with Solvent MeNO₂

The construction of multisubstituted β-pyrrolinones from simple starting materials remains a great challenge. Recently, a novel Cu(I)-catalyzed [2 + 2 + 1] cycloaddition reaction was developed for rapid access to fully substituted β-pyrrolinones, which are difficult to synthesize through traditional methods as this approach may involve unusual C-nucleophilic addition of enamines and umpolung of imines. Elucidating the reaction mechanism may inspire the development of new methodologies via the unusual C-nucleophilic addition of enamines and imines. However, the reaction mechanism is still unclear because none of the intermediates was observed during the reaction process. In this work, we employed theoretical and computational chemistry to investigate the possible pathway. Finally, the calculated results indicate that ketene formed by the Wolff rearrangement of α-diazo-β-ketoester reacts with enamine formed by the addition of alkynes and amine, affording the five-membered azaheterocycle, and this process involves the formation of a six-membered ring intermediate and sequential isomerization, and the further dehydrogenation needs to be assisted with solvent MeNO2