Molecular Interactions Research Articles

Polymorphism of candidate genes MTNR1B C/G (rs10830963) and TCF7L2 C/T (rs7903146) in children as a risk factor for the development of hepatobiliary system pathology in conditions of contamination of biological media with heavy metals (using lead as an example)

Introduction. Lead impact on health considering likely pathways of its molecular interactions in the body have not been given sufficient attention by researchers. The aim of this study was to assess polymorphism of the MTNR1B C/G (rs10830963) and TCF7L2 C/T (rs7903146) genes in children as a risk factor of hepatobiliary pathology in case of heavy metal contamination in biological media (exemplified by lead). Materials and methods. We examined ninety three 3–6 years children (39 children had hepatobiliary pathology and 54 children were considered healthy) who were exposed to low-dose airborne lead (0.1MPLa.d.), the average daily dose being 0.4 ∙ 10–3 µg/kg ∙ day. We estimated frequency of alleles and genotypes of the candidate genes MTNR1B C/G (rs10830963) and TCF7L2-1 C/T (rs7903146) associated with levels of lead contamination in biological media and hepatobiliary pathology. Results. The children from the observation group were established to have authentically high frequency of the G allele (OR=1.92, CI: 1.04–3.54) and GG genotype (OR=7.80, CI: 1.58–38.51; p<0.05) of the MTNR1B gene, as well as C wild type allele (OR=2.07, CI: 1.02–4.20; p<0.05) and CC genotype (OR=2.42, CI: 1.02–5.70; p<0.05) of the TCF7L2-1 gene, which were risk factors (RR=1.20–1.43) of developing hepatobiliary pathology aggravated by lead contamination in blood. Limitations. Limited sampling, the need to verify the results in further observations. Conclusion. The study established children with hepatobiliary pathology who lived under long-term low-dose exposure to airborne lead at the dose of 0.4 ∙ 10–3 µg/kg ∙ day (0.1MPLa.d.) to have elevated lead levels in blood and impaired biorhythms of smooth muscles in the bile duct combined with the risk (RR=1.20–1.43) of developing hepatobiliary pathology in carriers of G allele (OR=1.92, CI: 1.04–3.54; p<0.05) of the MTNR1B gene as well as C wild type allele (OR=2.07, CI: 1.02–4.20; p<0.05) of the TCF7L2-1 gene.

Analysis of kallikrein-related peptidase 7 (KLK7) autolysis reveals novel protease and cytokine substrates.

Kallikrein-related peptidase 7 (KLK7) is one of 15 members of the tissue kallikrein family and is primarily expressed in the skin epidermis. The activity of KLK7 is tightly regulated by multiple stages of maturation and reversible inhibition, similar to several other extracellular proteases. In this work, we used protease-specific inhibitors and active sitevariants to show that KLK7 undergoes autolysis at two separate sites in the 170 and 99 loops (chymotrypsinogen numbering), resulting in a loss of enzymatic activity. A protein BLAST search using the autolyzed KLK7 loop sequences identified mast cell chymase as a potential KLK7 substrate. Indeed, KLK7 cleaves chymase resulting in a concomitant loss of activity. We further demonstrate that KLK7 can hydrolyze other mast cell proteases as well as several cytokines. These cytokines belong mainly to the interferon and IL-10 families including IFN-α, IFN-β, IFN-γ, IL-28A/IFN-λ2, IL-20, IL-22, and IL-27. This is the first study to identify a possible molecular interaction link between KLK7 and mast cell proteases and cytokines. Although the precise biological implications of these findings are unclear, this study extends our understanding of the delicate balance of proteolytic regulation of enzyme activity that maintains physiological homeostasis, and facilitates further biological investigations.

Molecular Interactions Between ZnO Nanoparticles and Liver Target Proteins Revealed by Molecular Docking Method

Molecular Interactions Between ZnO Nanoparticles and Liver Target Proteins Revealed by Molecular Docking Method

Spectroscopic Investigation of Hydrogels Formed from Phenylalanine.

Supramolecular hydrogels assembled from amino acids, particularly offer promising prospects as biomimetic three-dimensional extracellular matrices. Phenylalanine, an aromatic amino acid, can self-assemble via hydrophobic interactions, notably through 𝜋 - 𝜋 stacking between phenyl rings. Although the self-assembly processes have been studied, the gelation mechanism of phenylalanine as an individual amino acid has received limited attention in the literature. This study focuses on investigating the gelation behavior of phenylalanine. Fluorescence spectroscopy, along with UV- Visible spectroscopy, and Fourier-transform infrared spectroscopy, were employed to elucidate the molecular interactions and the self-assembly process responsible for hydrogel formation. By leveraging fluorescence spectroscopy, this study aims to elucidate the mechanisms underlying the hydrogelation process. The fluorescence properties of the synthesized hydrogels are extensively examined, providing insights into their structural organization and stability, In this study, we employed a simple heating-cooling method for preparing phenylalanine hydrogel resulting in the formation of opaque hydrogels. Spectral analyses revealed the molecular interactions and structural organization, highlighting the relationship between concentration, opacity, and gel properties. Through this study, we investigated the gelation mechanism of a simple molecule using fluorescence spectroscopy, which provides a foundation for exploring the use of the same in other hydrogel-forming systems.

Integrating traditional QSAR and read-across-based regression models for predicting potential anti-leishmanial azole compounds.

Leishmaniasis, a neglected tropical disease caused by various Leishmania species, poses a significant global health challenge, especially in resource-limited regions. Visceral Leishmaniasis (VL) stands out among its severe manifestations, and current drug therapies have limitations, necessitating the exploration of new, cost-effective treatments. This study utilized a comprehensive computational workflow, integrating traditional 2D-QSAR, q-RASAR, and molecular docking to identify novel anti-leishmanial compounds, with a focus on Glycyl-tRNA Synthetase (LdGlyRS) as a promising drug target. A feature selection process combining Genetic Function Approximation (GFA)-Lasso with Multiple Linear Regression (MLR) was used to characterize 99 azole compounds across ten structural classes. The baseline MLR model (MOD1), containing seven simple and interpretable 2D features, exhibited robust predictive capabilities, achieving an R2train value of 0.82 and an R2test value of 0.87. To further enhance prediction accuracy, three qualified single models (two MLR and one q-RASAR) were used to construct three consensus models (CMs), with CM2 (MAEtest = 0.127) demonstrating significantly higher prediction accuracy for test compounds than the MOD1. Subsequently, Support Vector Regression (SVR) and Boosting yielded 0.88 (R2train), 0.86 (R2test), 0.92 (R2train), and 0.82 (R2test), respectively. Molecular docking highlighted interactions of potent azoles within the QSAR dataset with critical residues in the LdGlyRS active site (Arg226 and Glu350), emphasizing their inhibitory potential. Furthermore, the pIC50 values of an accurate external set of 2000 azole compounds from the ZINC20 database were simultaneously predicted by CM2 + SVR + Boosting models and docked against the LdGlyRS, which identified Bazedoxifene, Talmetacin, Pyrvinium, Enzastaurin as leading FDA candidates, whereas three novel compounds with the database code ZINC000001153734, ZINC000011934652, and ZINC000009942262 displayed stable docked interactions and favourable ADMET assessments. Subsequently, Molecular Dynamics (MD) simulations for 100ns were conducted to validate the findings further, offering enhanced insights into the stability and dynamic behaviour of the ligand-protein complexes. The integrated approach of this study underscores the efficacy of 2D-QSAR modelling. It identifies LdGlyRS as a promising leishmaniasis target, offering a robust strategy for discovering and optimizing anti-leishmanial compounds to address the critical need for improved treatments.

Unveiling Interactions between Self-Assembling Peptides and Neuronal Membranes.

The use of self-assembling peptide hydrogels in the treatment of spinal cord and brain injuries, especially when combined with adult neural stem cells, has shown great potential. To advance tissue engineering, it is essential to understand the effect of mechanochemical signaling on cellular differentiation. The elucidation of the molecular interactions at the level of the neuronal membrane still represents a promising area of investigation for many drug delivery and tissue engineering applications. An innovative molecular dynamics framework has been introduced to investigate the effect of SAP fibrils with different charges on neural membrane lipid domain dynamics. Such advance enables the in silico exploration of the biomimetic properties of SAP hydrogels and other polymeric biomaterials for tissue engineering applications.

Bioavailability and molecular recognition between secondary metabolites of Euphorbia hirta L. and 5-lipoxygenase using fragment molecular orbital method and pair interaction energy decomposition analysis

Is presented the bioavailability analysis for seven secondary metabolites from Euphorbia hirta L. (Euphorbiaceae). The bioactivity score, the molecular similarity analysis for each secondary metabolite, and the molecular docking 5-LOX/metabolite complex are also presented. For the similarity analysis, it is referenced the structure of allosteric LOX-5 inhibitor 3-acetyl-11-keto-beta-boswellic acid (AKBA). The fragment molecular orbital method (FMO) and pair interaction energy decomposition analysis (PIEDA) were applied to evaluate the interaction energy between secondary metabolites and the 5-LOX active site. Log P values of all the secondary metabolites studied were found to be higher than 5, contrary to what was expected with Lipinski’s rules of five. The reference LOX-5 ligand has a high electrostatic potential similarity with most secondary metabolites studied, with values from 0.667 to 0.730. Both AKBA and metabolites ligands were wedged between the two domains of LOX-5, and the main residues contact were LEU-66, ARG-68, VAL-110, HIS-130, ILE-126, GLN, 129, and LYS-133. The PIEDA analysis showed that stabilization in the 5-LOX active site is mainly dominated by hydrophobic interactions, with values up to -35 Kcal/mol. Due to the low presence of terminal-OH groups, electrostatic origin, and charge transfer interaction energies are also important but have values of less than 20 Kcal/mol.

Upconversion-Linked Immunosorbent Assay for the Biomimetic Detection of the Mycotoxin Cyclopiazonic Acid.

The neurotoxin α-cyclopiazonic acid (CPA) is an emerging mycotoxin produced as a secondary metabolite by several fungi species (i.e., Penicillium spp. and Aspergillus spp.). CPA commonly contaminates maize, crops, cheese, and wine. In this work, CPA detection in foodstuff was accomplished by the innovative integration of two strategies: upconversion nanoparticles (UCNPs) and epitope-mimicking peptides, to develop a competitive upconversion-linked immunosorbent assay (ULISA). We have applied UCNPs (type NaYF4:Yb3+, Er3+) as background-free optical labels due to their anti-Stokes shift with excitation in the near-infrared region and emission in the ultraviolet-visible region. Moreover, a CPA epitope-mimicking cyclic peptide (A2) was used as a substitute for the toxin-conjugates traditionally applied to competitive assays. UCNPs were decorated with an anti-CPA fragment antigen-binding antibody (UCNP-Fab), and CPA detection was achieved through competition with a biotinylated CPA epitope-mimicking cyclic peptide (A2-biotin, ACNWWDLTLC-GGGSK (Biotin)-NH2), anchored to a streptavidin-coated microtiter plate, for antibody binding. The ULISA platform offers ultrasensitive detection of CPA (limit of detection of 1.3 pg mL-1 and IC50 value of 15 pg mL-1), and no cross-reactivity was observed with other coproduced mycotoxins. These results substantially outperformed the analytical features of conventional heterogeneous immunoassays based on enzymatic detection. Additionally, the use of advanced computational tools, such as MOE and Alphafold AI, proved advantageous in elucidating the molecular interactions between the antibody and the epitope, providing insights that enhance the rational design of immunoassays. The proposed ULISA was applied to detect CPA in spiked maize samples, and the results were validated by high-performance liquid chromatography coupled to a tandem mass spectrometry detector (HPLC-MS/MS).

Chemodiversity and Molecular Mechanism Between Per-/Polyfluoroalkyl Substance Complexation Behavior of Humic Substances in Landfill Leachate

Landfill leachate contains a range of organic and inorganic pollutants, including per-/polyfluoroalkyl substances (PFASs), which can infiltrate into surrounding soil and groundwater through leaching processes, and can pose a threat to human health via food chains and drinking water processes. Thus, the transport of PFASs in landfill leachate is a research hotspot in environmental science. This study investigates the complexation and adsorption mechanisms between humic substances and PFASs in landfill leachate at the molecular level. Experimental results demonstrate that the binding constant logKsv of humic substances with PFASs correlates positively with specific ultraviolet absorbance (SUVA254), absorbance ratio (A250/A365), humification index (HIX), and fluorescence index (FI), while it exhibits a negative correlation with the biological index (BIX). These findings indicate that high aromaticity is a prerequisite for molecular interactions between humic substances and PFASs, with polar functional groups further facilitating the interaction. Molecular-level analysis revealed that humic substances undergo complexation and adsorption with PFASs through hydrophobic interactions, van der Waals forces, hydrogen bonding, ionic bonding, and covalent bonding, by functional groups such as hydroxyl, aliphatic C-H bonds, aromatic C=C double bonds, amides, quinones, and ketones. Future efforts should focus on enhanced co-regulation and mitigation strategies addressing the combined pollution of PFASs and humic substances in landfill leachate.

Edge-aware interactive refinement network for strip steel surface defects detection

Edge-aware interactive refinement network for strip steel surface defects detection

Design Chemical Exchange Saturation Transfer Contrast Agents and Nanocarriers for Imaging Proton Exchange in Vivo.

Chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) enables the imaging of many endogenous and exogenous compounds with exchangeable protons and protons experiencing dipolar coupling by using a label-free approach. This provides an avenue for following interesting molecular events in vivo by detecting the natural protons of molecules, such as the increase in amide protons of proteins in brain tumors and the concentration of drugs reaching the target site. Neither of these detections require metallic or radioactive labels and thus will not perturb the molecular events happening in vivo. Yet, magnetization transfer processes such as chemical exchange and dipolar coupling of protons are sensitive to the local environment. Hence, the use of nanocarriers could enhance the CEST contrast by providing a relatively high local concentration of contrast agents, considering the portion of the protons available for exchange, optimizing the exchange rate, and utilizing molecular interactions. This review provides an overview of these factors to be considered for designing efficient CEST contrast agents (CAs), and the molecular events that can be imaged using CEST MRI during disease progression and treatment, as well as the nanocarriers for drug delivery and distribution for the evaluation of treatments.

Single-molecule diffusivity quantification in Xenopus egg extracts elucidates physicochemical properties of the cytoplasm

The living cell creates a unique internal molecular environment that is challenging to characterize. By combining single-molecule displacement/diffusivity mapping (SMdM) with physiologically active extracts prepared from Xenopus laevis eggs, we sought to elucidate molecular properties of the cytoplasm. Quantification of the diffusion coefficients of 15 diverse proteins in extract showed that, compared to in water, negatively charged proteins diffused ~50% slower, while diffusion of positively charged proteins was reduced by ~80 to 90%. Adding increasing concentrations of salt progressively alleviated the suppressed diffusion observed for positively charged proteins, signifying electrostatic interactions within a predominately negatively charged macromolecular environment. To investigate the contribution of RNA, an abundant, negatively charged component of cytoplasm, extracts were treated with ribonuclease, which resulted in low diffusivity domains indicative of aggregation, likely due to the liberation of positively charged RNA-binding proteins such as ribosomal proteins, since this effect could be mimicked by adding positively charged polypeptides. Interestingly, in extracts prepared under typical conditions that inhibit actin polymerization, negatively charged proteins of different sizes showed similar diffusivity suppression consistent with our separately measured 2.22-fold higher viscosity of extract over water. Restoring or enhancing actin polymerization progressively suppressed the diffusion of larger proteins, recapitulating behaviors observed in cells. Together, these results indicate that molecular interactions in the crowded cell are defined by an overwhelmingly negatively charged macromolecular environment containing cytoskeletal networks.

The SLR1-OsMADS23-D14 module mediates the crosstalk between strigolactone and gibberellin signaling to control rice tillering.

Strigolactones (SLs) and gibberellins (GAs) have been found to inhibit plant branching or tillering, but molecular mechanisms underlying the interplay between SL and GA signaling to modulate tillering remain elusive. We found that the transcription factor OsMADS23 plays a crucial role in the crosslink between SL and GA signaling in rice tillering. Loss-of-function mutant osmads23 shows normal axillary bud formation but defective bud outgrowth, thus reducing the tiller number in rice, whereas overexpression of OsMADS23 significantly increases tillering by promoting tiller bud outgrowth. OsMADS23 physically interacts with DELLA protein SLENDER RICE1 (SLR1), and the interaction reciprocally stabilizes each other. Genetic evidence showed that SLR1 is required for OsMADS23 to control rice tillering. OsMADS23 acts as an upstream transcriptional repressor to inhibit the expression of SL receptor gene DWARF14 (D14), and addition of SLR1 further enhances OsMADS23-mediated transcriptional repression of D14, indicating that D14 is the downstream target gene of OsMADS23-SLR1 complex. Moreover, application of exogenous SL and GA reduces the protein stability of OsMADS23-SLR1 complex and promotes D14 expression. Our results revealed that SLs and GAs synergistically inhibit rice tillering by destabilizing OsMADS23-SLR1 complex, which provides important insights into the molecular networks of SL-GA synergistic interaction during rice tillering.

Microscopic Origins of Flow Activation Energy in Biomolecular Condensates.

The material properties of biomolecular condensates govern their dynamics and functions by influencing the molecular diffusion rates and biochemical interactions. A recent report has identified a characteristic timescale of temperature-dependent viscosity in biomolecular condensates arising from an activated dissociation events collectively referred to as flow activation energy. The microscopic origin of this activation energy is a complex function of sequence, stoichiometry, and external conditions. In this study, we elucidate the microscopic origins of flow activation energy in single and multicomponent condensates formed from model peptide sequences with varying "sticker" and "spacer" motifs, incorporating RNA as a secondary component. We examined how condensate density, RNA stoichiometry, and peptide sequence patterning impact these properties through detailed sequence-resolved coarse-grained simulations. Our findings reveal that flow activation energy is closely tied to the lifetime of sticker-sticker interactions under specific conditions. However, the presence of multiple competing stickers may complicate this relationship leading to frustrated interactions in condensates and lowering of activation energy. The findings of this study should help to create predictive models of material properties of condensates, which in turn can facilitate a more profound understanding of functions and programmable design principles of biomolecular condensates.

SGK1-Mediated Vascular Smooth Muscle Cell Phenotypic Transformation Promotes Thoracic Aortic Dissection Progression.

The occurrence of thoracic aortic dissection (TAD) is closely related to the transformation of vascular smooth muscle cells (VSMCs) from a contractile to a synthetic phenotype. The role of SGK1 (serum- and glucocorticoid-regulated kinase 1) in VSMC phenotypic transformation and TAD occurrence is unclear. Four-week-old male Sgk1F/F (Sgk1 floxed) and Sgk1F/F;TaglnCre (smooth muscle cell-specific Sgk1 knockout) mice were administered β-aminopropionitrile monofumarate for 4 weeks to model TAD. The SGK1 inhibitor GSK650394 was administered daily via intraperitoneal injection to treat the mouse model of TAD. Immunopurification and mass spectrometry were used to identify proteins that interact with SGK1. Immunoprecipitation, immunofluorescence colocalization, and GST (glutathione S-transferase) pull-down were used to detect molecular interactions between SGK1 and SIRT6 (sirtuin 6). RNA-sequencing analysis was performed to evaluate changes in the SIRT6 transcriptome. Quantitative chromatin immunoprecipitation was used to determine the target genes regulated by SIRT6. Functional experiments were also conducted to investigate the role of SGK1-SIRT6-MMP9 (matrix metalloproteinase 9) in VSMC phenotypic transformation. The effect of SGK1 regulation on target genes was evaluated in human and mouse TAD samples. Sgk1F/F;TaglnCre or pharmacological blockade of Sgk1 inhibited the formation and rupture of β-aminopropionitrile monofumarate-induced TADs in mice and reduced the degradation of the ECM (extracellular matrix) in vessels. Mechanistically, SGK1 promoted the ubiquitination and degradation of SIRT6 by phosphorylating SIRT6 at Ser338, thereby reducing the expression of the SIRT6 protein. Furthermore, SIRT6 transcriptionally inhibits the expression of MMP9 through epigenetic modification, forming the SGK1-SIRT6-MMP9 regulatory axis, which participates in the ECM signaling pathway. Additionally, our data showed that the lack of SGK1-mediated inhibition of ECM degradation and VSMC phenotypic transformation is partially dependent on the regulatory effect of SIRT6-MMP9. These findings highlight the key role of SGK1 in the pathogenesis of TAD. A lack of SGK1 inhibits VSMC phenotypic transformation by regulating the SIRT6-MMP9 axis, providing insights into potential epigenetic strategies for TAD treatment.

Experimental approaches to investigate biophysical interactions between homeodomain transcription factors and DNA.

Homeodomain transcription factors (TFs) bind to specific DNA sequences to regulate the expression of target genes. Structural work has provided insight into molecular identities and aided in unraveling structural features of these TFs. However, the detailed affinity and specificity by which these TFs bind to DNA sequences is still largely unknown. Qualitative methods, such as DNA footprinting, Electrophoretic Mobility Shift Assays (EMSAs), Systematic Evolution of Ligands by Exponential Enrichment (SELEX), Bacterial One Hybrid (B1H) systems, Surface Plasmon Resonance (SPR), and Protein Binding Microarrays (PBMs) have been widely used to investigate the biochemical characteristics of TF-DNA binding events. In addition to these qualitative methods, bioinformatic approaches have also assisted in TF binding site discovery. Here we discuss the advantages and limitations of these different approaches, as well as the benefits of utilizing more quantitative approaches, such as Mechanically Induced Trapping of Molecular Interactions (MITOMI), Microscale Thermophoresis (MST) and Isothermal Titration Calorimetry (ITC), in determining the biophysical basis of binding specificity of TF-DNA complexes and improving upon existing computational approaches aimed at affinity predictions.

Repurposing Drugs for Infectious Diseases by Graph Convolutional Network with Sensitivity-Based Graph Reduction.

Computational systems biology employs computational algorithms and integrates diverse data sources, such as gene expression profiles, molecular interactions, and network modeling, to identify promising drug candidates through repurposing existing compounds in response to urgent healthcare needs. This study tackles the urgent need for rapid therapeutic development against emerging infectious diseases. We introduce a novel analytic expression for sensitivity analysis based on the Kronecker product and enhance model prediction performance using Graph Convolutional Networks (GCNs) with sensitivity-based graph reduction. Our algorithm refines prediction performance by leveraging sensitivity-based graph reduction. By integrating RNA-seq data, molecular interactions, and GCNs, we identify disease-related genes and pathways, construct heterogeneous graph models, and predict potential drugs. This approach involves novel analytical expressions that assess sensitivity to model loss, employing the Kronecker product approach. Subgraph analysis identifies nodes for removal, leading to a refined graph used for model retraining. This cost-effective pipeline focuses on computational methods for drug repurposing, targeting infectious diseases such as Zika virus and COVID-19 infection. Applied to these infections, our methodology integrates 659 proteins and 703 drugs for Zika virus, and 495 proteins and 468 drugs for COVID-19, along with their interactions derived from gene expression profiles. Top candidate drugs, such as Betamethasone phosphate and Bizelesin for Zika virus, and Chloroquine, Heparin Disaccharide, and Resveratrol for COVID-19, were validated through literature review or docking analysis. This scalable approach demonstrates promise in repurposing drugs for urgent healthcare challenges.

Crystalline Assemblies of DNA Nanostructures and Their Functional Properties

AbstractSelf‐assembly presents a remarkable approach for creating intricate structures by positioning nanomaterials in precise locations, with control over molecular interactions. For example, material arrays with interplanar distances similar to the wavelength of light can generate structural color through complex interactions like scattering, diffraction, and interference. Moreover, enzymes, plasmonic nanoparticles, and luminescent materials organized in periodic lattices are envisioned to create functional materials with various applications. Focusing on structural DNA nanotechnology, here, we summarized the recent developments of two‐ and three‐dimensional lattices made purely from DNA nanostructures. We review DNA‐based monomer design for different lattices, guest molecule assembly, and inorganic material coating techniques and discuss their functional properties and potential applications in photonic crystals, nanoelectronics, and bioengineering as well as future challenges and perspectives.

Room temperature phosphorescent wood hydrogel

Room temperature phosphorescent (RTP) hydrogels exhibit great potential but show poor mechanical performance (Tensile strengthen <1 MPa) and non-tunable RTP performance, hindering their practical applications. Here, we develop wood hydrogel (W-hydrogel) by the in situ polymerization of acrylamide in the presence of delignified wood. As a result of the molecular interactions between the components of delignified wood and polyacrylamide, the W-hydrogel exhibit a tensile strengthen of 38.4 MPa and green RTP emission with a lifetime of 32.5 ms. Moreover, the tensile strength and RTP lifetime are increased to 153.8 MPa and 69.7 ms, upon treating W-hydrogel with ethanol. Significantly, the mechanical and RTP performance of W-hydrogel is switched by alternating “ethanol and water” treatments. Additionally, W-hydrogel is used as energy donor in order to produce red afterglow emission using RhB via an energy transfer process. Taking advantage of these properties, W-hydrogel is processed into multiple hydrogel-based luminescent materials.

A simple synthesis of supramolecular Polyamide12 via solid‐state melt reaction and its interlaminar properties in Carbon Fiber Reinforced Thermoplastics

AbstractDespite the exceptional mechanical properties of epoxy‐based carbon fiber‐reinforced plastic (CFRP), its commercial potential is limited due to high production costs and manufacturing difficulties. As a promising alternative, thermoplastic‐based CFRP (CFRTP) offers simpler manufacturing, lower cost, and recyclability. This study presents a strategy to overcome challenges for CFRTP manufacturing by using a low molecular weight (MW) thermoplastic that forms high‐MW assemblies via dynamic molecular interactions. A quadruple hydrogen‐bonding unit (UPy)‐end functional polyamide (PA‐UPy) was synthesized by simple solid‐state melt reaction of powdered mixture of PA12 and UPy‐containing isocyanate. An increase in tensile properties was observed with an increase in crystallinity by the adoption of UPy moiety. The adoption of PA‐UPy in CFRTP, prepared by simply stacking the powder and CF fabric followed by hot pressing, enhanced the composite's tensile and interlaminar properties. Therefore, this process is proposed as a simple and effective method to improve the mechanical properties of CFRTP.Highlights Synthesis of PA‐UPy achieved via solid‐state melt reaction of PA and UPy. PA supramolecular structure boosts tensile strength and modulus of films and CFRTP. UPy‐NCO doubles the interlaminar shear strength of PA‐UPy‐based CFRTP.