Abstract Time-dependent aging phenomena in polymer adsorption at solid–liquid interfaces from dilute solutions were discovered over three decades ago. However, how the properties of a single polymer chain evolve over macroscopic timescales remains poorly understood. Here, we conducted a long-term experimental study on polyethylene glycol (PEG) chains adsorbed from ultradilute solutions by complementarily using single-molecule fluorescence tracking, liquid-environment atomic force microscopy, and sum-frequency generation vibrational spectroscopy. We observe distinctly nonequilibrium and aging dynamics in individual adsorbed polymer chains. Immediately after adsorption, the polymer conformations exhibit a coexistence of states with both low and high segment–surface contact, which display significantly different desorption timescales. The observed time-dependent aging phenomenon can be attributed to the probabilistic formation of distinct conformations upon adsorption, rather than from postadsorption rearrangements. This behavior is well rationalized by a nonergodic continuous-time random walk model. This suggests that ergodicity breaking underlies the nonequilibrium polymer dynamics at solid–liquid interfaces under ultradilute conditions.

The spatial heterogeneity of pathological factors in diabetic chronic wounds (DCWs) limits the development of effective treatment strategies. Here, a hydrogel-based wound dressing integrated with a dissolving microneedle array (H@MN) that orchestrates a novel spatiotemporal cascade reaction strategy is presented. Compared to the classical temporal cascade reaction, the spatiotemporal cascade reaction is characterized by spatially compartmentalized catalysts, which rely on the cross-regional diffusion of initial reaction products to the subsequent catalyst site to drive the sequential catalytic processes. Targeting the pathological features of DCWs, the glucose oxidase (GOX)-, superoxide dismutase (SOD)-, and catalase (CAT)-catalytic reactions are selected, which are catalyzed by natural enzymes or nanozymes. By integrating these catalysts into a spatiotemporal cascade reaction within the H@MN, it can intervene in and dynamically modulate the pathological factors in different spatial domains of DCWs at various temporal stages. Both in vitro and in vivo experiments confirm that the H@MN-enabled spatiotemporal cascade reaction, when combined with photothermal therapy, achieves superior healing efficacy in DCWs. The H@MN-enabled spatiotemporal cascade reaction is believed to inspire a generalizable strategy for treating diverse diseases characterized by spatially varied pathological microenvironments, offering a promising paradigm for advanced therapeutics.

The distribution of training data is a fundamental yet often overlooked factor governing the success of machine learning models in materials science. This study evaluates the influence of data distribution on predictive modeling by benchmarking seven static and adaptive sampling strategies across high-dimensional benchmark functions and the real-world materials database. The core finding is that sampling strategies that simultaneously focus on both positive and negative extremum regions significantly enhance model generalization, outperforming both uniform sampling and unidirectional strategies that target only one extremum region (either positive or negative). These results suggest that actively shaping the data distribution to explore "undesirable" material regions is neither a waste of resources nor just marginally beneficial. Instead, it is a well-considered move that paves the way for a more efficient data-driven discovery workflow.

The adsorption of charged nanoparticles at water-oil interfaces constitutes a fundamental phenomenon, underlying pivotal technologies spanning from emulsion stabilization to the sophisticated fabrication of foams. However, the diffusional behavior of these nanoparticles remains poorly understood. Here, we use single-molecule tracking experiments to show that the diffusion of like-charged nanoparticles at the water-oil interface not only becomes anomalous but also displays a diffusional aging phenomenon at the interfacial coverage that is not associated with the glassy state. We further develop a theoretical framework that quantitatively reproduces all experimental observations. Molecular dynamics simulations reveal the necessity of the coexistence of attraction and repulsion for the emergence of aging dynamics. The interplay between attraction and repulsion leads to nanoparticle adhesion taking place over observable timescales, which is manifested as aging dynamics. The discovery of diffusional aging demonstrates that interfacial evolution persists beyond adsorption equilibrium, suggesting that this effect must be accounted for in applications involving water-oil interfaces laden with charged nanoparticles.

Elucidating the dynamic mechanisms of polymer translocation through nanochannels with channel oscillation characterized by periodic opening and closing is critical for advancing the understanding of polymer transport in confined environments and guiding the design of advanced nanofluidic systems. We employed coupled molecular dynamics and multi-particle collision dynamics simulations to investigate the influence of channel oscillation on polymer capture and translocation in varying dielectric environments. The capture probability and translocation time of polymers consistently exhibit a non-monotonic dependence on oscillation frequency. Translocation is accelerated within a certain range of the reduced oscillation frequency , with the translocation time reaching a minimum in the interval of 10-1 to 100, where  is defined as the ratio of the translocation time through a static channel to the oscillation period. This interval corresponds to the regime where the oscillation period is commensurate with the timescale of polymer translocation. Analysis indicates that periodic opening and closing of the channel generates a microflow toward the trans side via hydrodynamic interactions, driving monomers into the channel during opening and facilitating their expulsion during channel closure, thereby accelerating capture and translocation. Furthermore, it modulates polymer conformation, enhancing the driving force on polymers and further promoting translocation. Conversely, electrostatic interactions impede these processes by altering polymer conformation and introducing steric hindrance from condensed counterions. These findings reveal fundamental mechanisms of polymer dynamics in oscillatory channels and may provide insights into systems where such dynamics are a key factor, from biological pores to the design of synthetic nanochannels.

Vanadium-based cathodes for aqueous zinc-ion batteries (AZIBs) face critical challenges in practical capacity and low-current-density cycling stability. Herein, a synergistic strategy is introduced that overcomes these limitations through the co-engineering of an activatable bulk precursor and a dynamic in situ-formed interface. A porous, V3+-rich 0.3CaV2O4-0.7V2O3 heterostructure (CaVO-4) specifically designed to undergo a profound in situ electrochemical activation into highly active phases is first constructed. Concurrently, by leveraging supplemental SO4 2- in the electrolyte, a stable CaSO42H2O cathode-electrolyte interphase (CEI) layer is formed in situ via reaction with Ca2+ released during cycling. By serving a dual role, the CEI ensures structural durability and simultaneously enables the intrinsic kinetics of the bulk. This "bulk-to-interface" synergy manifests in electrochemical performance, including 89.3% capacity retention over 300 cycles at 0.5 A g-1, an extraordinary rate capability of 424.4 mAh g-1 at 20 A g-1, and a high specific capacity of 479.2 mAh g-1 at 0.2 A g-1. Advanced characterizations, including in situ XRD and ex situ XPS/XAFS, combined with DFT calculations, unravel the synergistic mechanisms underpinning the enhanced Zn2+ storage. This work pioneers a paradigm that unites rational bulk activation with interfacial self-optimization, providing a strategy for durable, high-performance cathodes in advanced energy storage.

Both Fickian-but-not-Gaussian diffusion (FnGD) and anomalous diffusion have been observed in various heterogeneous systems. It remains unclear whether FnGD is an independent diffusion process and what factors determine whether anomalous diffusion or FnGD will be observed. Here, we studied two well-defined heterogeneous systems. The first system involves the simulation of polymer diffusion within polymer-nanoparticle mixtures (exhibiting temporal and population heterogeneity), and the second system involves single-molecule fluorescence tracking experiments of nanoparticle diffusion in inverse opals (exhibiting spatial heterogeneity). Despite the qualitative physical differences between these two systems, different types of diffusion, including anomalous diffusion, FnGD, and Brownian diffusion can emerge at varying time scales provided the system is ergodic. The observed phenomena are contingent upon the specific observation time window. Within the same system, diffusion that emerged at different time scales can be interpreted through different diffusion models. These observations suggest that future research should consider characterization across multiple time scales to fully elucidate the underlying mechanisms of heterogeneous systems.

Treating androgenetic alopecia (AGA) with platelet-rich plasma (PRP) holds great promise; however, effective and comfortable delivery remains a challenge. Direct injection causes pain, and PRP-incorporated microneedles (MNs) have low hardness and slow dissolution. To tackle this problem, we propose a machine-learning (ML)-driven strategy, which involves integrating the selection of therapeutic substances, orthogonal experiment designs, ML prediction, and Pareto front identification. Through the implementation of only 18 experiments based on orthogonal experiment designs, this ML-assisted strategy can pinpoint an optimal material composition that concurrently attains high hardness and rapid dissolution. We utilized this optimal material composition to fabricate MNs, and their biological functionality was demonstrated through multiple aspects, including the sustained release of various growth factors over 30 days, more than 90% bacterial inhibition, reactive oxygen species scavenging, and the promotion of the proliferation of dihydrotestosterone-damaged human dermal papilla cells. In vivo studies indicated significant hair regrowth in AGA mice through the activation of the Wnt/β-catenin pathway, outperforming the effects of minoxidil. Significantly, this approach eliminates the biosafety risks associated with the use of synthetic materials. The developed framework is anticipated to serve as a generalizable paradigm for expediting the clinical translation of biomaterials such as MNs.

The traditional trial-and-error approach, although effective, is inefficient for optimizing rubber composites. The latest developments in machine learning (ML)-assisted methodologies are also not suitable for predicting and optimizing rubber composite properties. This is due to the dependency of the properties on processing conditions, which prevents the alignment of data collected from different sources. In this work, a novel workflow called the ML-enhanced trial-and-error approach is proposed. This approach integrates orthogonal experimental design with symbolic regression (SR) to effectively extract empirical principles. This combination enables the optimization process to retain the characteristics of the traditional trial-and-error approach while significantly improving efficiency and capability. Using rubber composites as the model system, the ML-enhanced trial-and-error approach effectively extracts empirical principles encapsulated by high-frequency terms in the SR-derived mathematical formulas, offering clear guidance for material property optimization. An online platform has been developed that allows for no-code usage of the proposed methodology, designed to seamlessly integrate into the existing experimental optimization process.

Monomer friction in trapped polymers is a key determinant of the fundamental time scales governing a wide range of dynamic and kinetic processes in physics, chemistry, and biology. In this paper, we present a theoretical investigation of the monomer friction of individual Rouse chains trapped in a harmonic potential. Our analysis is based on the friction memory function within the framework of the generalized Langevin equation (GLE). The friction memory function comprises contributions from both solvent friction (assumed to be constant and independent of the external potential) and intra-chain friction. We demonstrate that the external potential induces an additional harmonic potential by modifying the correlations between monomers. This modification, in turn, alters the friction memory function. Our analyses of the induced potentials and relaxation time spectra reveal a characteristic chain length N c, which describes the unperturbed size of the harmonically confined chain. In the long chain limit (chain length N >> N c >> 1), the time-dependent monomer friction function exhibits universal power-law behaviors in the mediate time scale. Specifically, the exponent decreases from 1/2 to 0 as the ratio k '/k (where k ' is the external harmonic potential strength and k is the bond spring strength) increases. This behavior aligns with dynamic scaling arguments. In the long time limit, the friction function reaches a plateau, with the value varying from N c gamma/2 for k '/k << 1 to the solvent friction gamma for k '/k >> 1. These results indicate that the external potential enhances monomer diffusion by reducing intra-chain friction. This finding provides a fundamental understanding of the dynamics of trapped polymers and highlights the crucial role of external potentials in modifying intra-chain interactions and monomer mobility.

Germination of many crop species is improved by priming, which facilitates pre-germinative metabolism through controlled hydration. However, priming is often associated with reduced seed longevity. Here, a screen of Arabidopsis thaliana DNA repair mutants identified dna ligase 6 and dna ligase 4 (lig6lig4) seeds as most sensitive to ageing of primed seed. Genetic analysis of wild type and lig6lig4 mutants provided mechanistic insight into the link between DNA double strand break (DSB) repair and longevity of primed seeds. RNAseq analysis of naturally aged seeds demonstrated that, while the transcriptome changes in primed aged seeds mirrors the enhancement of germination, priming significantly activated the transcriptional response to chromosomal breaks and, in lig6lig4 mutant seed, greatly exacerbated programmed cell death. These results revealed that DSB repair is an important factor in promoting longevity of primed seed, further supported by the improved longevity of primed seeds with enhanced expression of LIG6. Collectively our findings establish the genetic requirement for LIG6 in longevity of primed seed and indicate that the reduced longevity of primed seeds is mitigated by DSB repair activities. These results provide insight into the molecular basis of the reduced longevity of primed seed, important for sustainable crop production under changing climates.

Tooth whitening has attracted considerable attention as it can enhance appearance and improve oral health. Nanocatalysts with peroxidase-like activity can catalyze H2O2 to generate reactive oxygen species (ROS), a process known as chemodynamic therapy (CDT). The ROS generation can achieve effective tooth whitening and caries prevention. Nonetheless, traditional CDT methods often struggle with controlling the reaction process by adjusting the concentrations of H2O2 or nanocatalysts. An excessive ROS can harm oral tissues, whereas insufficient ROS may compromise therapeutic efficacy. To address this issue, this study designed a hydrogel bilayer that separately encapsulates H2O2 and iron-based metal-organic frameworks (Fe-MOFs) nanoparticles (NPs) with peroxidase-like activity. The ROS generation was regulated by leveraging the concentration-gradient diffusion of H2O2. Through Monte Carlo simulations and machine learning algorithms, mathematical formulas were derived to elucidate how to harness concentration-gradient diffusion for near-independent modulation of the reaction half-life and rate. The experimental results demonstrated that being guided by the formulas could effectively avoid the initial burst of ROS and manipulate the ROS generation duration, thereby achieving safe and effective tooth whitening and caries prevention. We anticipate that this bilayer design strategy can be extended to other CDT systems, enabling precise control over therapeutic outcomes.

Oral biofilms are associated with various oral diseases causing pain and discomfort, and pose a severe threat to general health. Conventional surgical debridement and antibacterial therapy often yield unsatisfactory outcomes because they either fail to fully and painlessly eliminate biofilms or increase the risk of bacterial resistance. In this study, we synthesized polydopamine-embellished Zn-MOFs (ZIF-8@PDA NPs), which can degrade under mildly acidic conditions to release Zn2+. These nanoparticles also convert near-infrared light energy into heat, thereby enabling synergistic photothermal and antibacterial metal ion therapy for oral biofilm eradication. Our findings reveal that therapy with ZIF-8@PDA NPs, when exposed to near-infrared radiation, demonstrates exceptional antibacterial efficacy and is highly effective in eradicating oral biofilms both in vitro and ex vivo. Furthermore, we used an in vivo rodent tooth biofilm model to demonstrate the suppression of dental caries. This work presents a promising solution for preventing and suppressing dental caries as well as other treating diseases linked to oral biofilm infections.

Early embryo loss affects all mammalian species, including humans, and agriculturally important food-producing mammals such as cattle. The developing conceptus (embryo and extraembryonic membranes) secretes proteins that can modify the endometrium and can be critical for early pregnancy processes, such as maternal recognition of pregnancy (MRP) or enhancing uterine receptivity to implantation. For example, a competent bovine conceptus secretes interferon tau (IFNT) to initiate MRP. The bovine conceptus also secretes other proteins at the time of MRP, including CAPG and PDI, which are highly conserved among placental mammals. We have previously shown that these proteins act upon the endometrium to modulate receptivity, embryo development, and implantation in species with different implantation strategies (humans and cattle). We hypothesize that developing a novel 3D bovine endometrium-on-a-chip system will enhance our understanding of the role of conceptus-derived factors in altering the endometrium and/or uterine luminal fluid (ULF) secretion. Here, we have developed a 3D bovine endometrium-on-a-chip system, comprising both stromal and epithelial cell culture combined with culture medium flow. This system better mimics the in vivo endometrium, and endometrial exposure to conceptus-derived factors, than conventional 2D endometrial cell culture. We have demonstrated that the conceptus-derived proteins, CAPG and PDI, modulate the endometrial transcriptome and secretory response to promote pathways associated with early pregnancy and alter ULF composition. This work highlights the critical need for more robust and in vivo-like culture systems to study endometrial-conceptus interactions in vitro to further investigate the role of conceptus-derived factors for pregnancy success.

This study presents a method for in situ analysis of the adsorption and desorption of polymers on the nanoparticle surface within entangled polymer solutions. This method is based on the principle that when a polymer adsorbs onto the nanoparticle surface, the diffusion coefficient of the polymer becomes equivalent to that of the nanoparticle. Consequently, adsorption events can be identified by properly detecting diffusion-state transitions in trajectories acquired through single-molecule fluorescence tracking experiments. This method, which involves numerically generated trajectories, training of a 1D convolutional neural network (1D-CNN), and state prediction, was validated experimentally. When the nanoparticle-to-polymer diffusion coefficient ratio is as high as 0.5, the trained 1D-CNN model can still achieve 85% accuracy and an F1 score of 0.86 in adsorption-state identification. These results significantly outperform those of the hidden Markov model and the threshold-based method. Using the proposed method, we found that in aqueous solutions containing entangled poly(ethylene glycol) (PEG) chains and silica nanoparticles of varying sizes, the adsorption probability of PEGs onto the nanoparticle surface decreases, while the adsorption duration increases as the nanoparticle size decreases.

Theories predicted that shear promotes desorption, but due to the presence of factors such as aggregation effects, it is difficult to observe how shear influences the adsorption and desorption of individual protein molecules. In this study, we employed high-throughput single-molecule tracking and molecular dynamics simulations to investigate how shear flow affects the adsorption kinetics of plasma proteins (including human serum albumin, immunoglobulin G, and fibrinogen) at solid-liquid interfaces. Over the studied shear rate range of 0 - 103 s-1, shear stress did not trigger the protein desorption. Notably, we observed a significant increase, up to two orders of magnitude, in the adsorption rate constants ka, in the dilute limit at solid-liquid interfaces. However, this shear-induced increase in ka diminished with increasing the protein concentrations. At least in the scenarios studied, these trends were consistent across all three types of proteins and two types of surfaces investigated. Through a systematic analysis combining control experiments, coarse-grained, and all-atom molecular dynamics simulations, we identified that the shear-induced increase in ka could be attributed to enhanced protein rotational diffusion, thereby increasing the likelihood of favorable surface proximity for adsorption.

Recent experiments have shown that hole traps could be suppressed in polymer light-emitting diodes under current stress by diluting the light-emitting conjugated polymers within an “inert” large-bandgap host material. However, it is unclear why there is an enhanced dilution effect in partially miscible blends rather than fully miscible blends, as intuition would suggest that better miscibility leads to better dilution. In this work, we propose a cascade analysis by combining multiple fluorescence microscopic techniques and all-atom molecular dynamics simulations to study the solid-to-solid dilution of poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (MEH-PPV) in MEH-PPV/polystyrene (PS) blends and MEH-PPV/poly(vinylcarbazole) (PVK) blends. By varying the molecular weights of PS and PVK, we can regulate their miscibility with MEH-PPV. The results corroborate that the dilution effect is enhanced in partially miscible blends rather than fully miscible ones. This is because, in partially miscible blends undergoing phase separation, the concentration of MEH-PPV is notably decreased in the phase occupying the majority of the volume, leading to an overall greater dilution effect than in fully miscible blends. Moreover, MEH-PPV could adopt the more extended conformation in the fully miscible blend, causing a shorter intermolecular distance to further undermine the dilution effect. These findings explain the seemingly counterintuitive more effective dilution effect observed in the recently reported partially miscible blends and provide guidance for further enhancing the performance of future generations of polymer light-emitting diodes.

ABSTRACT Pregnancy establishment in mammals requires a complex sequence of events, including bi-lateral embryo-maternal communication, leading up to implantation. This is the time when most pregnancy loss occurs in mammals (including humans and food production species) and dysregulation in embryo-maternal communication contributes to pregnancy loss. Embryo-derived factors modify the function of the endometrium for pregnancy success. We hypothesise that these previously unexplored conceptus-derived proteins may be involved in altering the function of the endometrium to facilitate early pregnancy events in mammals with different early pregnancy phenotypes. Here, we show that protein disulphide-isomerase (PDI) is a highly conserved protein among mammals, and provide evidence for a species-specific roles for PDI in endometrial function in mammals with different implantation strategies. We show how PDI alters the endometrial transcriptome in human and bovine in vitro in a species-specific manner, and using a microfluidic approach we demonstrate that it alters the secretome capability of the endometrium. We also provide evidence from in vitro assays using human-derived cells that MNS1, a transcript commonly downregulated in response to PDI in human and bovine endometrial epithelial cells, may be involved in the attachment (but not invasion) phase of implantation. We propose that the trophoblast-derived protein PDI, is involved in supporting the modulation of the uterine luminal fluid secreted by the endometrium to support conceptus nourishment, and also in the process of embryo attachment to the uterine lumen for pregnancy success in mammals. SIGNIFICANCE STATEMENT We provide evidence that a highly conserved protein (PDI) alters the endometrial transcriptome in a species- and cell-specific manner. Exposure of endometrial epithelia to PDI altered genes belonging to immune modulatory, pro-inflammatory, and adhesion-pathways. One transcript, MNS1, was commonly downregulated in endometrial epithelia from species with superficial (bovine) and invasive (human) implantation morphologies. Knockdown of MNS1 expression in humans epithelia altered the ability of human trophoblast BeWo spheroids to attach suggesting a mechanism by which PDI affects implantation in human and bovine. In addition, using a microfluidics approach we have shown that PDI alters the secretome in a species-specific manner demonstrating PDI alters a key function of the endometrium in mammals.