Aggregation Kinetics Research Articles

Single point mutations at the S129 residue of α-synuclein and their effect on structure, aggregation, and neurotoxicity.

Parkinson's disease is an age-related neurological disorder, and the pathology of the disease is linked to different types of aggregates of α-synuclein or alpha-synuclein (aS), which is an intrinsically disordered protein. The C-terminal domain (residues 96-140) of the protein is highly fluctuating and possesses random/disordered coil conformation. Thus, the region plays a significant role in the protein's solubility and stability by an interaction with other parts of the protein. In the current investigation, we examined the structure and aggregation behavior of two artificial single point mutations at a C-terminal residue at position 129 that represent a serine residue in the wild-type human aS (wt aS). Circular Dichroism (CD) and Raman spectroscopy were performed to analyse the secondary structure of the mutated proteins and compare it to the wt aS. Thioflavin T assay and atomic force microscopy imaging helped in understanding the aggregation kinetics and type of aggregates formed. Finally, the cytotoxicity assay gave an idea about the toxicity of the aggregates formed at different stages of incubation due to mutations. Compared to wt aS, the mutants S129A and S129W imparted structural stability and showed enhanced propensity toward the α-helical secondary structure. CD analysis showed proclivity of the mutant proteins toward α-helical conformation. The enhancement of α-helical propensity lengthened the lag phase of fibril formation. The growth rate of β-sheet-rich fibrillation was also reduced. Cytotoxicity tests on SH-SY5Y neuronal cell lines established that the S129A and S129W mutants and their aggregates were potentially less toxic than wt aS. The average survivability rate was ∼40% for cells treated with oligomers (presumably formed after 24h of incubation of the freshly prepared monomeric protein solution) produced from wt aS and ∼80% for cells treated with oligomers obtained from mutant proteins. The relative structural stability with α-helical propensity of the mutants could be a plausible reason for their slow rate of oligomerization and fibrillation, and this was also the possible reason for reduced toxicity to neuronal cells.

A federated transfer learning method with low-quality knowledge filtering and dynamic model aggregation for rolling bearing fault diagnosis

Intelligent mechanical fault diagnosis techniques have been extensively developed in recent years. Owing to the advantage of data privacy protection, federated learning has recently received increasing attention; this approach can utilize monitoring data from multiple local clients to train an optimal global diagnosis model. However, low-quality data are often present for some clients, including mislabeled data and incomplete data that lack some health states. Furthermore, the data distributions are usually different across different clients owing to variations in machine operating conditions. Therefore, the performance of the federated diagnostic model may be limited by low-quality data and data distribution discrepancies. To address this issue, a federated transfer learning method with low-quality knowledge filtering and dynamic model aggregation is proposed. First, a dynamic filter is designed by filtering out low label probabilities predicted by low-quality source domain models to construct high-confidence pseudo-labels for the target domain data. Then, the batch normalized maximum mean discrepancy (BN-MMD) distance metric is introduced into the training loss function to reduce the data distribution discrepancy between the source clients and the target client without private data leakage. While building the global model in each training round, a dynamic model aggregation algorithm is proposed to mitigate the influence of low-quality clients. This algorithm evaluates the weight of each client according to its contribution to the total consensus diagnostic knowledge and then aggregates the local models with adaptive weights. Consequently, it can overcome the drawback of the classical federated averaging (FedAvg) algorithm, where all local clients are assigned the same weight when constructing the global model. Experiments are conducted on three bearing datasets under various loads and speeds. Compared with some existing diagnostic methods, the proposed federated transfer learning method can reduce the impact of low-quality data and achieve higher diagnostic accuracy while preserving data privacy.

Characterization of the effect of chromium salts on tropocollagen molecules and molecular aggregates

Though the capability of chromium treatment to improve the stability and mechanical properties of collagen fibrils is well-known, the influence of different chromium salts on collagen molecules (tropocollagen) is not well characterized. In this study, the effect of Cr3+ treatment on the conformation and hydrodynamic properties of collagen was studied using atomic force microscopy (AFM) and dynamic light scattering (DLS). Statistical analysis of contours of adsorbed tropocollagen molecules using the two-dimensional worm-like chain model revealed a reduction of the persistence length (i.e., the increase of flexibility) from ≈72 nm in water to ≈56–57 nm in chromium (III) salt solutions. DLS studies demonstrated an increase of the hydrodynamic radius from ≈140 nm in water to ≈190 nm in chromium (III) salt solutions, which is associated with protein aggregation. The kinetics of collagen aggregation was shown to be ionic strength dependent. Collagen molecules treated with three different chromium (III) salts demonstrated similar properties such as flexibility, aggregation kinetics, and susceptibility to enzymatic cleavage. The observed effects are explained by a model that considers the formation of chromium-associated intra- and intermolecular crosslinks. The obtained results provide novel insights into the effect of chromium salts on the conformation and properties of tropocollagen molecules.

Mapping charge-transfer excitations in Bacteriochlorophyll dimers from first principles

Photoinduced charge-transfer excitations are key to understand the primary processes of natural photosynthesis and for designing photovoltaic and photocatalytic devices. In this paper, we use Bacteriochlorophyll dimers extracted from the light harvesting apparatus and reaction center of a photosynthetic purple bacterium as model systems to study such excitations using first-principles numerical simulation methods. We distinguish four different regimes of intermolecular coupling, ranging from very weakly coupled to strongly coupled, and identify the factors that determine the energy and character of charge-transfer excitations in each case. We also construct an artificial dimer to systematically study the effects of intermolecular distance and orientation on charge-transfer excitations, as well as the impact of molecular vibrations on these excitations. Our results provide design rules for tailoring charge-transfer excitations in Bacteriochloropylls and related photoactive molecules, and highlight the importance of including charge-transfer excitations in accurate models of the excited-state structure and dynamics of Bacteriochlorophyll aggregates.

Spatiotemporal velocities, aggregation, and false dispersion: numerical considerations for the modeling of colonial and motile harmful algae

PurposeThe purpose of this study is to investigate the errors arising from the numerical treatment of model processes, paying particular attention to the impact of key system features including widely variable dispersion coefficients, spatiotemporal velocities of algal cells, and the aggregation of algae from single cells to large colonies. An advection–dispersion model has been presented to describe the vertical transport of colonial and motile harmful algae in a lake environment.Design/methodology/approachModel performance is examined for two different numerical treatments of the advective term: first-order upwind and quadratic upwind with a stability-preserving flux limiter (SMART). To determine how these schemes impact predictions, comparisons are made across a sequence of models with increasing complexity.FindingsUsing first-order upwinding for advection–dispersion calculations with a time oscillating velocity field leads to oscillatory numerical dispersion. Subjecting an initially uniform distribution of large-sized algal colonies to a spatiotemporal velocity creates a concentration pulse, which reaches a steady-state width at high-grid Peclet numbers when using the SMART scheme; the pulse exhibits contraction–expansion behavior throughout a velocity cycle at all Peclet numbers when using first-order upwinding. When aggregation dynamics are included with advection-dominated spatiotemporal transport, results indicate the SMART scheme predicts larger peak concentration values than those predicted by first-order upwind, but peak location and the time to large colony appearance remain largely unchanged between the two advective schemes.Originality/valueTo the best of the authors’ knowledge, this study is the first numerical investigation of a novel advection–dispersion model of vertical algal transport. In addition, a generalized expression for the effective dispersion coefficient of temporally variable flow fields is presented.

Managing soil organic matter through biochar application and varying levels of N fertilisation increases the rate of water-stable aggregates formation

Abstract The formation of soil aggregates, including water-stable aggregates, is linked to soil organic matter (SOM). Biochar (B) is carbon-rich, which, in addition to storing carbon in a stable form for many years, has important benefits for soils and plants, but the mechanisms of soil structure formation after B and mineral fertiliser application are not sufficiently studied. For this reason, the study aimed to answer the following questions: How (1) the rate of B and (2) varying levels of nitrogen fertiliser (N) being applied to the soil affect the dynamics of soil aggregation due to the increase in the content of soil organic carbon, labile carbon in the bulk soil and in the content of water-stable aggregates (WSA) size-fractions. In 2014–2021, in Dolná Malanta (experimental site of Slovak University of Agriculture on silty loam Haplic Luvisol) during the growing seasons, soil samples were collected from all the B (0, 10 and 20 t ha–1) and N (0, 1st and 2nd level of N fertilisation) treatments. The results have shown that the highest values of many variables were associated with B20 treatment for all the N fertilisation levels. B compared to N more significantly affected the content of almost all the size-fractions of WSA. In all the treatments, the content of WSAma >5 mm, 5–3 mm, 3–2 mm and 1–0.5 mm in size was increasing over time – a yearly increase from 0.31 to 2.14% for 8-years. Based on the changes in the SOM content, WSA were divided into 3 groups: 1) Water-stable microaggregates (WSAmi < 0.25 mm), 2) Smaller size-fractions of water-stable macroaggregates (WSAma 1–0.25 mm), and 3) Medium and large fractions of WSAma (WSAma ≥1 mm).

Reciprocal effects of NOM and solution electrolyte ions on aggregation of ferrihydrite nanoparticles

The effects of natural organic matter (NOM) types and electrolyte ions are crucial to the aggregation of ferrihydrite nanoparticles (Fh NPs) in the environment. Dynamic light scattering (DLS) was employed for the aggregation kinetics of Fh NPs (10 mg/L as Fe) in the present study. The critical coagulation concentration (CCC) values of Fh NPs aggregation in NaCl were obtained in the presence of 15 mg C/L NOM as SRHA (857.4 mM) > PPHA (752.3 mM) > SRFA > (420.1 mM) > ESHA (141.0 mM) > NOM-free (125.3 mM), indicating Fh NPs aggregation was inhibited as the above order. Comparatively in CaCl2, the CCC values were measured in ESHA (0.9 mM), PPHA (2.7 mM), SRFA (3.6 mM), SRHA (5.9 mM), NOM-free (76.6 mM), implying NPs aggregation was enhanced following the order of ESHA > PPHA > SRFA > SRHA. To investigate the dominant mechanisms, the aggregation of Fh NPs was comprehensively studied under the effects of NOM types, concentrations (0–15 mg C/L) and electrolyte ions (NaCl/CaCl2 beyond CCC). In NaCl/CaCl2, the low concentration of NOM (<7.5 mg C/L) could accelerate NPs aggregation mainly due to patch-charge attraction. When NOM concentration was high (> 7.5 mg C/L), the inhibition effect on NPs aggregation occurred in NaCl due to steric repulsion, whereas the enhancement effect in CaCl2 of aggregation was dominated by the bridging effect. The results indicated that the effects of NOM types, concentration and electrolyte ions should be carefully considered for the environmental behavior of NPs.

Twisted Structures in Natural and Bioinspired Molecules: Self-Assembly and Propagation of Chirality Across Multiple Length Scales.

Several biomolecules can form dynamic aggregates in water, whose nanometric structures often reflect the chirality of the monomers in unexpected ways. Their twisted organization can be further propagated to the mesoscale, in chiral liquid crystalline phases, and even to the macroscale, where chiral, layered architectures contribute to the chromatic and mechanical properties of various plant, insect, and animal tissues. At all scales, the resulting organization is determined by a subtle balance among chiral and nonchiral interactions, whose understanding and fine-tuning is fundamental also for applications. We present recent advances in the chiral self-assembly and mesoscale ordering of biological and bioinspired molecules in water, focusing on systems based on nucleic acids or related aromatic molecules, oligopeptides, and their hybrid stuctures. We highlight the common features and key mechanisms governing this wide range of phenomena, together with novel characterization approaches.

A molecular dynamics approach for a parametric study of colloidal suspension aggregation kinetics

A molecular dynamics approach for a parametric study of colloidal suspension aggregation kinetics

Experimental and modeling approaches applied to the whey proteins and vitamin B9 complexes study

In this work, complexes of β-lactoglobulin (βlg) or whey protein isolate (WPI) with folic acid (FA) were developed as potential food ingredients. A dilute concentrations regime was employed to elucidate possible binding sites of the vitamin on the protein. The ζ potential, the aggregation kinetics and the particle size distributions were studied. On the other hand, in silico studies were carried. Additionally, the ability of the mixed systems to preserve the vitamin bioaccessibility was assessed by exposing the protein-FA systems to in vitro digestion. The ζ potential study showed similar values for the pure proteins and the mixed systems, obtaining for the highest concentrations studied (0.01825% W/W) values of: 21 ± 1 and 29 ± 2 mV for βlg and βlg-FA, and 22 ± 1 and 23 ± 2 mV for WPI and WPI-FA. These results suggest that the interactions between FA and proteins are of the hydrophobic type. The aggregation kinetics showed that the process of formation of protein-FA was slower than the formation of pure FA crystals. The particle size distributions showed different sizes between the pure proteins and those of the mixed systems. Regarding in silico studies, it was found that βlg presents regions where hydrogen bonding interactions between FA and certain amino acids of the protein prevail. Finally, regarding the bioaccessibility of the vitamin, WPI-FA was the system that obtained the highest value (92%). These complexes could be used as ingredients to be incorporated into foods consumed by people with special diets such as pregnant women.

Dynamics and Composition of Small Heat Shock Protein Condensates and Aggregates

Small heat shock proteins (sHSPs) are essential ATP-independent chaperones that protect the cellular proteome. These proteins assemble into polydisperse oligomeric structures, the composition of which dramatically affects their chaperone activity. The biomolecular consequences of variations in sHSP ratios, especially inside living cells, remain elusive. Here, we study the consequences of altering the relative expression levels of HspB2 and HspB3 in HEK293T cells. These chaperones are partners in a hetero-oligomeric complex, and genetic mutations that abolish their mutual interaction are associated with myopathic disorders.HspB2 displays three distinct phenotypes when co-expressed with HspB3 at varying ratios. Expression of HspB2 alone leads to formation of liquid nuclear condensates, while shifting the stoichiometry towards HspB3 resulted in the formation of large solid-like aggregates. Only cells co-expressing HspB2 with a limited amount of HspB3 formed fully soluble complexes that were distributed homogeneously throughout the nucleus. Strikingly, both condensates and aggregates were reversible, as shifting the HspB2:HspB3 balance in situ resulted in dissolution of these structures.To uncover the molecular composition of HspB2 condensates and aggregates, we used APEX-mediated proximity labelling. Most proteins interact transiently with the condensates and were neither enriched nor depleted in these cells. In contrast, we found that HspB2:HspB3 aggregates sequestered several disordered proteins and autophagy factors, suggesting that the cell is actively attempting to clear these aggregates. This study presents a striking example of how changes in the relative expression levels of interacting proteins affects their phase behavior. Our approach could be applied to study the role of protein stoichiometry and the influence of client binding on phase behavior in other biomolecular condensates and aggregates.

Aggregation kinetics and stability of biodegradable nanoplastics in aquatic environments: Effects of UV-weathering and proteins

Plastic pollution caused by conventional plastics has promoted the development and use of biodegradable plastics. However, biodegradable plastics do not degrade readily in water; instead, they can generate micro- and nanoplastics. Compared to microplastics, nanoplastics are more likely to cause negative impacts to the aquatic environment due to their smaller size. The impacts of biodegradable nanoplastics highly depend on their aggregation behavior and colloidal stability, which still remain unknown. Here, we studied the aggregation kinetics of biodegradable nanoplastics made of polybutylene adipate co-terephthalate (PBAT) in NaCl and CaCl2 solutions as well as in natural waters before and after weathering. We further studied the effect of proteins on aggregation kinetics with both negative-charged bovine serum albumin (BSA) and positive-charged lysozyme (LSZ). For pristine PBAT nanoplastics (before weathering), Ca2＋ destabilized nanoplastic suspensions more aggressively than Na+, with the critical coagulation concentration being 20 mM in CaCl2 vs 325 mM in NaCl. Both BSA and LSZ promoted the aggregation of pristine PBAT nanoplastics, and LSZ showed a more pronounced effect. However, no aggregation was observed for weathered PBAT nanoplastics under most experimental conditions. Further stability tests demonstrated that pristine PBAT nanoplastics aggregated substantially in seawater, but not in freshwater, and only slightly in soil pore water; while weathered PBAT nanoplastics remained stable in all natural waters. These results suggest that biodegradable nanoplastics, especially weathered biodegradable nanoplastics, are highly stable in the aquatic environment, even in the marine environment.

Glucagon-like peptide 1 aggregates into low-molecular-weight oligomers off-pathway to fibrillation

The physical stability of peptide-based drugs is of great interest to the pharmaceutical industry. Glucagon-like peptide 1 (GLP-1) is a 31-amino acid peptide hormone, the analogs of which are frequently used in the treatment of type 2 diabetes. We investigated the physical stability of GLP-1 and its C-terminal amide derivative, GLP-1-Am, both of which aggregate into amyloid fibrils. While off-pathway oligomers have been proposed to explain the unusual aggregation kinetics observed previously for GLP-1 under specific conditions, these oligomers have not been studied in any detail. Such states are important as they may represent potential sources of cytotoxicity and immunogenicity. Here, we identified and isolated stable, low-molecular-weight oligomers of GLP-1 and GLP-1-Am, using size-exclusion chromatography. Under the conditions studied, isolated oligomers were shown to be resistant to fibrillation or dissociation. These oligomers contain between two and five polypeptide chains and they have a highly disordered structure as indicated by a variety of spectroscopic techniques. They are highly stable with respect to time, temperature, or agitation despite their noncovalent character, which was established using liquid chromatography-mass spectrometry and sodium dodecyl sulfate-polyacrylamide gel electrophoresis. These results provide evidence of stable, low-molecular-weight oligomers that are formed by an off-pathway mechanism which competes with amyloid fibril formation.

Dynamic Process Modeling and Real-Time Performance Evaluation of Rework Production System With Small-Lot Order

Rework production system is a typical structure in practical manufacturing, where the defective parts detected by the inspection machine are sent to rework rather than being directly scrapped. Due to the special structure, more complex coupling phenomena between machines and buffers are introduced, especially when machines are unreliable and buffers are finite. In addition, under the intelligent manufacturing environment, customized demands trigger small-lot orders become a common occurrence, which lead to traditional steady-state analysis inapplicable. Therefore in this paper, we study dynamic process modeling and real-time performance evaluation problems of the rework system. Practical issues, such as unreliable machines, finite buffers, and small-lot orders are taken into account. Specifically, a novel dynamic decomposition and aggregation algorithm is proposed. The proposed method is validated to have a precise performance measures prediction effect, as well as an efficient computational performance.

Efficient Asynchronous Federated Learning Research in the Internet of Vehicles

Federated Learning (FL) is a distributed machine learning paradigm that ensures data do not leave local devices. Data sharing problems can be addressed by FL in untrusted environments, e.g., the Internet of Vehicles (IoV). However, FL needs to frequently exchange massive parameters to achieve preset model goals. In addition, the change in bandwidths and the delay of data communications due to user mobility challenge the synchronization of model parameters. In this paper, an Efficient Hierarchical Asynchronous Federated Learning (EHAFL) algorithm is proposed to adjust the encoding length dynamically according to the bandwidth and reduce the communication cost substantially. A dynamic hierarchical asynchronous aggregation mechanism is proposed leveraging gradient sparsification and asynchronous aggregation techniques to further reduce the communication costs and improve the aggregation efficiency of the global model. Simulation results on MNIST and real-world datasets show that our proposed solution can reduce the communication costs by 98% while only compromising the model accuracy by 1%.

Dissecting how ALS-associated D290V mutation enhances pathogenic aggregation of hnRNPA2286–291 peptides: Dynamics and conformational ensembles

The aggregation of RNA binding proteins, including hnRNPA1/2, TDP-43 and FUS, is heavily implicated in causing or increasing disease risk for a series of neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS). A recent experimental study demonstrated that an ALS-related D290V mutation in the low complexity domain (LCD) of hnRNPA2 can enhance the aggregation propensity of wild type (WT) hnRNPA2286–291 peptide. However, the underlying molecular mechanisms remain elusive. Herein, we investigated effects of D290V mutation on aggregation dynamics of hnRNPA2286–291 peptide and the conformational ensemble of hnRNPA2286–291 oligomers by performing all-atom molecular dynamic and replica-exchange molecular dynamic simulations. Our simulations demonstrate that D290V mutation greatly reduces the dynamics of hnRNPA2286–291 peptide and that D290V oligomers possess higher compactness and β-sheet content than WT, indicative of mutation-enhanced aggregation capability. Specifically, D290V mutation strengthens inter-peptide hydrophobic, main-chain hydrogen bonding and side-chain aromatic stacking interactions. Those interactions collectively lead to the enhancement of aggregation capability of hnRNPA2286–291 peptides. Overall, our study provides insights into the dynamics and thermodynamic mechanisms underlying D290V-induced disease-causing aggregation of hnRNPA2286–291, which could contribute to better understanding of the transitions from reversible condensates to irreversible pathogenic aggregates of hnRNPA2 LCD in ALS-related diseases.

Research on time-varying dynamic response aggregation model of distributed generator participating in active distribution network

In order to solve the flexible management and control problem of a large number of distributed generators in the distribution system, a time-varying dynamic response aggregation model of distributed generators participating in active distribution network is proposed. First of all, a modular index system for DG cluster division is constructed, and the cluster is divided from two aspects of structure and function. In structure, distributed power generation is preliminarily divided based on electrical distance. In function, the cluster can achieve self-balance of power within the cluster and power complementation between clusters. Secondly, based on the time-varying scenario of distributed generation participating in active distribution network, considering the time coupling system, the distribution network mathematical model and distributed generation aggregation optimization model suitable for time-varying response are proposed. This method coordinates the upper and lower limits of power, the upper and lower limits of climbing rate, and the upper and lower limits of energy between distributed clusters. The distributed power aggregation model sends the air conditioning command in real time to achieve the power balance within the cluster and the power complementarity between clusters within the scope of safe power dispatching. Finally, the validity and correctness of this method are verified by IEEE33 nodes.

Influence of off-grid/grid-connected operation on stability of large-scale photovoltaic system

Off-grid or grid-connected operation of large-scale photovoltaic system may cause stability problems. When the system performs off-grid operation, energy storage, as balance node, regulates power and frequency, then also influences stability. Under grid-connected operation, the external power system balances power and frequency regulation, and energy storage only equilibrium wave power. Although a detailed model for a single photovoltaic generation system has been established, the connection of numerous photovoltaic units is difficult to model and simulate, and it can easily cause dimension disaster. In order to analyze stability effectively of off-grid/grid-connected operation of large-scale photovoltaic system, we first establish the equivalent model of a photovoltaic farm through the method of dynamic aggregation of wind turbines, and then obtain indicators affecting the stability considering the reactance matrix of the transmission line. When the real part of the oscillation mode sensitivity index is greater than zero, oscillation mode approaches the imaginary axis, indicating that the PV system stability deteriorates. Conversely, the PV system is regionally stable. Finally, the effects of the number of photovoltaic units and transmission line length on stability are theoretically analyzed, and the theoretical derivation is validated through simulations. More PV units and a longer transmission line increase the likelihood of instability through the sensitivity of the oscillation mode.

Photoelectromagnetic Responsive Adaptive Porous Frameworks through Dynamic Covalent Chemistry of Tetraarylethylene‐backboned Aryldicyanomethyl Radicals

AbstractDynamic materials undergoing adaptive solid‐state transitions are attractive for soft mechanics and information technology. Here, we report a novel porous framework system based on macrocyclic trimers assembled from open‐shell tetraarylethylene building blocks with aryldicyanomethyl radicals as coupling linkers. Under mechanical, thermal, or chemical stimuli, the framework showed adaptability by activating conformational dynamics and radical‐based transformations, thus displaying macroscopic responsiveness in terms of light absorption, luminescence, and magnetism. We studied the dynamic processes by variable‐temperature nuclear magnetic resonance (VT‐NMR), variable‐temperature electron spin resonance (VT‐ESR), and superconducting quantum interference device (SQUID) measurement and further established a proof‐of‐concept application for multi‐modal information encryption. The strategy may open avenues for rational design of solid‐state photoelectromagnetic dynamic materials by merging dynamic covalent coupling chemistry and functional aggregation principles.

Photoelectromagnetic Responsive Adaptive Porous Frameworks through Dynamic Covalent Chemistry of Tetraarylethylene-backboned Aryldicyanomethyl Radicals.

Dynamic materials undergoing adaptive solid-state transitions are attractive for soft mechanics and information technology. Here, we report a novel porous framework system based on macrocyclic trimers assembled from open-shell tetraarylethylene building blocks with aryldicyanomethyl radicals as coupling linkers. Under mechanical, thermal, or chemical stimuli, the framework showed adaptability by activating conformational dynamics and radical-based transformations, thus displaying macroscopic responsiveness in terms of light absorption, luminescence, and magnetism. We studied the dynamic processes by variable-temperature nuclear magnetic resonance (VT-NMR), variable-temperature electron spin resonance (VT-ESR), and superconducting quantum interference device (SQUID) measurement and further established a proof-of-concept application for multi-modal information encryption. The strategy may open avenues for rational design of solid-state photoelectromagnetic dynamic materials by merging dynamic covalent coupling chemistry and functional aggregation principles.