Physician Orders for Life-Sustaining Treatment (POLST) and Advance Directives (AD) aim to honor patient autonomy. However, the impact of the signatory's identity-whether the patient or a surrogate-on clinical trajectories in the intensive care unit (ICU) remains poorly characterized. To evaluate the association between signatory identity and terminal care intensity and hospitalization costs among adult patients in the ICU. This nationwide population-based cohort study utilized the South Korean National Health Insurance Service database, including 1,189,042 adult ICU admissions between 2020 and 2023. Statistical analyses employed high-dimensional fixed-effects models to account for institutional variability across 417 hospitals. Among 1,189,042 patients, surrogate-determined POLST (SD-POLST) was more than three times as prevalent as patient-determined POLST (PD-POLST). Among 90-day decedents, PD-POLST was associated with significantly reduced odds of invasive terminal care (OR, 0.43; 95% CI, 0.43-0.54). Conversely, SD-POLST more than doubled the odds (OR, 2.16; 95% CI, 1.98-2.35). Notably, even patients with proactive ADs experienced increased care intensity once a surrogate signed the final order (OR, 1.69; 95% CI, 1.51-1.89), indicating a phenomenon of "AD erosion." SD-POLST was also associated with significantly higher daily hospitalization costs (cost ratio, 1.04; 95% CI, 1.02-1.06) compared with no documentation. The clinical efficacy of POLST in limiting non-beneficial care depends fundamentally on the signatory. Surrogate-led decisions were associated with paradoxically higher care intensity and costs, potentially overriding prior patient wishes. These findings highlight the critical importance of early, patient-led discussions to ensure goal-concordant end-of-life care in the ICU.
The synergistic removal of NO and chlorinated volatile organic compounds (CVOCs) using bifunctional catalysts has emerged as a cutting-edge strategy in environmental catalysis. However, achieving both efficient NOx selective catalytic reduction and CVOCs catalytic oxidation remains fundamentally challenging due to the inherent trade-off between activity and selectivity. Herein, we demonstrate that this trade-off can be overcome by applying a mechanochemical strategy coupled with electronic band modulation to construct a novel heterojunction catalyst, in which MnCe oxides are integrated with piezoelectric BaTiO3 to form a heterojunction interface. The optimized TB-MnCe catalyst exhibits remarkable synergistic performance, achieving the synergistic removal of o-dichlorobenzene (>80%) and NOx (100%) within a broad temperature range of 250-350 °C. Combined experimental and theoretical investigations reveal an interfacial charge transfer of approximately 4.6 electrons from BaTiO3 to MnCe during mechanochemical treatment. This charge redistribution, mediated by the engineered interface, significantly enhances the redox capability of the active sites and promotes cooperative reactions. This work highlights that atomic-level interfacial electronic modulation induced by mechanochemical processing provides a powerful route to resolve the activity-selectivity dilemma in bifunctional catalysis.
Here we studied the aqueous transport of different alkali-metal ions in charged boron nitride nanotubes (BNNTs) and compared the results with those obtained in carbon nanotubes, using macroscopic, vertically aligned nanotube membranes at densities up to 107 pores cm-2. Our study reveals that ion transport in 3- and 12-nm-diameter charged BNNTs is fundamentally different from that in either carbon nanotubes of a similar size, or two-dimensional boron nitride nanochannels. We find two unexpected transport phenomena: ultrafast, cation-selective diffusion that exceeds Fickian diffusion up to 31-fold; and preferentially enhanced transport rates for Li+ over other alkali-metal ions (K+ and Na+) that are opposite to the ordering of their mobilities in bulk solution. We show that the overall fast transport of cations is due to diffusio-osmotic surface transport, while the preferentially enhanced transport of Li+ is believed to result from ion-specific interactions with the charged BNNTs. As a result of enhanced and cation-selective transport, the BNNT membranes produced per-pore osmotic-power densities up to 15,300 W m-2 in a 1 mM:1 M LiCl concentration gradient at pH 11. The energy-conversion efficiency approached the theoretical limit of 50% at pH 5.5. As a demonstration, we power a calculator, watch and light-emitting diode using 1-cm2 BNNT membranes in a salinity gradient. The unusual transport phenomena in BNNTs, as well as the flexible and scalable membrane-fabrication process, may enable ion-selective nanotube membranes optimized for lithium recovery, 'blue' osmotic energy and other separation and energy-conversion processes.
The evolution of soft robots into embodied intelligent systems relies fundamentally on precise proprioception. However, a universal solution for capturing continuous deformations during diverse interactions, particularly in spatially confined interventional scenarios, remains lacking. Here, we introduce a deep learning-enabled versatile shape perception method based on a single-ended multimode fiber (MMF). By leveraging the intrinsic integration advantages of optics, our minimalist reflective architecture physically eliminates the dependence on complex demodulation units and distal devices. Furthermore, treating chaotic optical speckle fields as data streams encoding high-dimensional shape information, reconfigurable neural decoders resolve a single physical channel into versatile perception modes tailored to heterogeneous tasks: discrete state confirmation on soft grippers (>99% accuracy), continuous shape tracking on bionic dexterous hands (~5-fold spatial resolution enhancement), and intuitive 3D morphological reconstruction of soft surgical robots (IoU>0.93). Overall, our work establishes a versatile framework for breaking hardware adaptability limits via computation, laying a solid foundation for closed-loop control in digital twins of soft robots.
ConspectusOrbital correlation diagrams are central to chemistry. Based on the symmetry compatibility and orbital overlap amplitude, they link the energy-ordered frontier molecular orbitals (MOs) of reactants and products and have long been a powerful and essential tool for understanding chemical interactions (reactions) and molecular properties. The frontier MOs typically include the highest occupied MOs (HOMOs) and the lowest unoccupied MOs (LUMOs), along with a few nearby orbitals of the reactants. However, it is also known that some reactions cannot be well explained with a few frontier MOs. The main drawback of traditional orbital correlation diagrams is that the orbital energies of the reactants shown in the diagram are calculated assuming they are in free, isolated states. But orbital energy levels can be significantly shifted by external fields and the existence of neighboring molecules. In other words, orbital energy levels can be notably reshuffled when we put reactants "physically" (via electrostatic interactions, Pauli repulsion, and van der Waals interactions) together, even without "chemical" interactions (via orbital mixtures or electron transfers).Here, we introduce a novel concept, "in situ" orbital correlation, and demonstrate its applications. This concept is based on our developed block-localized wave function (BLW), which is the simplest variant of ab initio valence bond (VB) theory. The uniqueness of the BLW method lies in its ability to derive orbital energies of a molecule self-consistently in the presence of other species or external fields, as a BLW solution essentially corresponds to a hypothetical diabatic (or resonance) state, a mathematical construct in which all electron transfers between interacting species are "disabled". In such a way, we can correlate orbitals by considering the field (physical) effects from neighboring species even without any orbital (chemical) interactions.This "in situ" orbital correlation concept was first proposed in the study of the activation mechanism of CO by the diboryne compound B2(NHCR)2, where we demonstrated that when CO approaches B2(NHCR)2, there is a HOMO-LUMO swap in B2(NHCR)2 primarily due to the Pauli repulsion from the carbon lone pair of CO, leading to the compatibility of HOMO and HOMO-1 of B2(NHCR)2 with both π* orbitals of CO. Since then, this concept has been adopted in much of our research. For instance, in our most recent study of NCCL- anions (L = N2, CO, CS), which exhibit notable geometric differences, "in situ" orbital correlation diagrams reveal an orbital swap in the fragment NCC- with the approach of the ligand L and subsequently confirm the C(0) theory proposed by the Frenking group. Previously, we explored the "anti-electrostatic" nature of the Al-Mg bond and confirmed that the bond is purely ionic. This contradicts the view from frontier orbitals of Al(I) and Mg compounds, which exhibit a perfect match for a dative covalent bond between them. Now, with the help of the "in situ" orbital correlation diagram, it becomes obvious that the metal-metal bond is a typical ionic bond, because when the Mg compound is brought close, the energy level of the HOMO of Al(I) compound decreases significantly, leading to a reversal of the HOMO-LUMO energy level order and the extension of the HOMO-LUMO band gap and subsequently minimal probability of any electron transfer. We expect that the novel concept of "in situ" orbital correlation will fundamentally enrich our understanding of chemical reactions, electron transfer pathways, and molecular bonding.
Soft magnetic actuators have gained significant interest for applications in minimally invasive medical robots, artificial muscles, soft robotic manipulators, and wearable bioelectronic interfaces, yet their functionality remains fundamentally limited by current magnetization strategies. To this end, a novel in-process printing and magnetization strategy with spatial and dynamic control of an external magnetic field during printing is developed to fabricate magnetorheological elastomers with fully customizable three-dimensional (3D) magnetization profiles. This method allows localized magnetic domain alignment in arbitrarily programmed orientations within a solid, enabling anisotropic actuation at micron to millimeter scales. The proposed method is highly sensitive to curing kinetics, material viscosity, and magnet positioning, which are characterized theoretically, experimentally, and in simulation. Structures magnetized in this way offer robust strain-sensing, information-encoding, and bio-inspired heterogeneous actuation capabilities. Demonstrations highlight this versatility, including a dragonfly with oppositely magnetized wings for tunable resonant actuation, an octopus-inspired swimmer whose magnetized legs reproduce aquatic locomotion, and a serpentine catheter with high degrees of freedom across 6 magnetic nodes. Together, these advances establish a versatile platform for designing magnetically responsive systems that couple programmable anisotropic actuation with biological complexity.
The clinical prognosis for osteosarcoma (OS) remains bottlenecked by chemoresistance and pulmonary metastasis. OS features dense infiltration by tumor‑associated macrophages (TAMs) that are hijacked into an immunosuppressive, pro-tumorigenic M2-like phenotype. Overcoming this therapeutic plateau requires a paradigm shift toward active remodeling of the tumor immune microenvironment. This review evaluates the trajectory of TAM-targeted interventions in OS, emphasizing the critical transition from monotypic phagocytosis checkpoint blockade (e.g., CD47, GD2) to multimodal synergistic regimens. We systematically dissect how next-generation nanomedicine, targeted metabolic stressors (ferroptosis, cuproptosis), and pharmacological rewiring can forcibly induce immunogenic cell death and reverse M2 polarization. Addressing the unique reconstructive demands of OS, we spotlight the development of immuno-regenerative scaffolds-bifunctional biomaterials engineered to synchronize post-resection tumor clearance with active osteogenesis. Finally, we highlight how spatial transcriptomics and biomimetic platforms are mapping physical immune-exclusion barriers and novel therapeutic subpopulations. Breaking the OS therapeutic stalemate ultimately demands interventions that breach these spatial architectures and fundamentally reprogram TAMs, guided by real-time functional imaging (e.g., ferumoxytol MRI) and high-resolution biomarkers (e.g., PSME2).
Neuroendovascular venous interventions are increasingly performed using technologies originally developed for arterial procedures and indications. However, the major dural venous sinuses possess a unique intraluminal anatomy that is not present in arteries, raising concerns about device-anatomy interactions that may affect procedural performance. We used a perfused human cadaveric model with direct intraluminal angioscopic visualization to evaluate currently available endovascular devices within the dural venous sinuses and to characterize mechanisms of device-anatomy interactions associated with technical difficulty and failure. Six fresh human head-and-neck cadaveric specimens were perfused with 0.9% saline solution via bilateral internal jugular vein catheterization using a peristaltic pump. Direct intraluminal angioscopic visualization was achieved through transcranial access to the major dural venous sinuses, allowing real-time observation of target segments during device manipulation. Standard endovascular maneuvers were performed within the dural venous sinuses, including guidewire and microcatheter navigation, catheter advancement, venous stent deployment, stent retriever deployment, aspiration thrombectomy, and balloon angioplasty. Angioscopic and fluoroscopic recordings were independently reviewed by experienced neurointerventionists to identify and categorize technical challenges and failure mechanisms. Angioscopy revealed multiple device-intraluminal interactions that were not fully appreciated on fluoroscopy alone. Several representative technical challenge and failure scenarios were identified and grouped into four principal mechanisms: (1) catheterization of venous channels parallel to the main sinus lumen, resulting in catheter entrapment and incomplete expansion of venous stents and stent retrievers; (2) device deformation or incomplete expansion due to intraluminal bands, including stent deformation, malposition, and constrained balloon angioplasty; (3) arrested or impaired device advancement caused by intraluminal bands, frequently necessitating microcatheter-assisted support to overcome ledge effects; and (4) interaction with arachnoid granulations leading to occlusion of aspiration catheter inlets and impeded intraluminal navigation. The venous system differs fundamentally from arteries in luminal geometry and internal architecture. Our findings demonstrate that arterial-derived devices incompletely accommodate these differences, resulting in parallel channel navigation, constrained expansion and deformation of stents, and occlusion of suction catheters. These findings highlight the fact that veins are not arteries and underscore the need for venous-specific techniques and technologies.
Accurate prediction of drug-target interactions (DTIs) is a fundamental challenge in early-stage drug discovery, particularly in the absence of reliable three-dimensional structural information. In this study, we propose a fully sequence-based DTI prediction framework that eliminates dependence on structural data while achieving docking-comparable predictive performance. The proposed framework introduces a unified representation that systematically integrates physicochemical protein descriptors, protein 3-gram sequence motifs, and sequence-like drug encodings into a single feature space, enabling effective learning across heterogeneous models. A diverse set of machine learning, deep learning, and ensemble classifiers is evaluated under stratified five-fold cross-validation with class imbalance correction using Synthetic Minority Over-sampling Technique (SMOTE). Beyond individual models, the framework incorporates advanced ensemble strategies, including a stacking classifier that combines Random Forest, Support Vector Machine, and Logistic Regression, resulting in robust performance with ROC-AUC values exceeding 0.90 and a maximum AUC of 0.914. Importantly, the framework explicitly addresses model interpretability through feature importance analysis, revealing biologically meaningful protein sequence motifs associated with binding interactions. To further substantiate the reliability of the proposed approach, molecular docking experiments are conducted on a subset of predicted drug-target pairs, and the observed agreement between docking scores and predicted binding probabilities provides independent validation. Collectively, this study demonstrates that carefully engineered sequence-derived representations, coupled with optimized ensemble learning, constitute a scalable, interpretable, and computationally efficient alternative to structure-dependent DTI prediction methods.
Maladaptive learned fear responses to stress underlie several debilitating neuropsychiatric disorders. Here, we identify a brain-to-spleen neural pathway that mediates learned fear through coordinated neuroimmune interactions. Using a chronic acquired olfactory stress (CAOS) model, we demonstrate that sustained enhancement of the piriform cortex (Pir) excitability contributes to the transformation of stress-associated olfactory inputs into learned fear-avoidance behavior. Through comprehensive neural tracing approaches, we mapped a functional tetrasynaptic circuit (Pir→ventral hippocampus CA1 subregion [vCA1]→CeM→DVC→spleen) regulating T helper 17 (Th17) cell-dependent fear responses. Single-nucleus RNA sequencing revealed that olfactomedin 3-expressing glutamatergic neurons in the Pir integrate olfactory stress inputs to activate this pathway. Importantly, targeted disruption of this circuit through either conditional knockdown of Olfm3 within Pir→vCA1 projecting glutamatergic neurons or chemogenetic inhibition of these projections eliminated CAOS-induced splenic Th17 cell expansion and fear avoidance. These findings provide fundamental insights into how learned fear becomes maladaptive by identifying a complete neural circuit linking olfactory perception to peripheral immunity.
Cellulose microfibrils (CMFs) in wood macrofibrils are semi-crystalline including crystalline and disordered regions, yet the mechanical role of disordered cellulose remains elusive. Here, we employed reactive molecular dynamics simulations to systematically investigate the mechanical role of disordered cellulose by developing atomic models of softwood macrofibrils with varying cellulose crystallinity. Simulation results showed that there is a critical balance between the strength and toughness of macrofibrils governed by the cellulose crystallinity. Lowering cellulose crystallinity decreased the longitudinal modulus and tensile strength of macrofibrils but increased the ultimate strain. In contrast, toughness exhibited a non-monotonic dependence on crystallinity and reached a peak at approximately 90%. Hydrogen-bond analysis revealed that disordered cellulose mainly led to fewer hydrogen bonds within CMFs, thereby weakening the strength of macrofibrils. Fracture analysis further revealed that disordered regions acted as crack initiation points and energy dissipation regions, making macrofibrils exhibit more ductile behavior. In addition, a theoretical model based on mixture rule incorporating the effect of interphase was proposed to predict the longitudinal moduli of macrofibrils. These findings provide fundamental molecular insights into the structure-property relationships of macrofibrils in wood secondary cell walls and shed light on the design of wood-based materials with tailored mechanical properties.
This study investigates the geochemical dynamics and ecological risks of rare earth elements (REE) in abandoned clay mining lakes in the second world's largest producer of ceramic tiles in Santa Gertrudes (CDSG), Brazil. Using a multi-technique approach, combining conventional filtration, diffusive gradients in thin films (DGT), single-particle inductively coupled mass spectrometry (spICP-MS), and geochemical modelling, a seasonal baseline was established and the influence of an atmospheric particulate deposition event associated with an unprecedent 2024 wildfire episode was evaluated. Results showed that seasonal variability produced relatively minor changes in REE behaviour, whereas the 2024 atmospheric deposition event promoted substantial shifts in REE partitioning. The median total concentration (∑REET) surged from 3,200 ng L-1 in 2022 to 25,800 ng L-1 during the 2024 event, with Cerium (Ce) reaching a peak of 12,500 ng L-1. A critical decoupling between fractions was observed: while the dissolved fraction (<0.45 μm) accounted for up to 82% of REEs in 2022, it dropped drastically to <1% in 2024, with DGT-measured lability largely varying across all campaigns. The detection of Ce-containing nanoparticles via spICP-MS (8.4×109 to 1.7×1010 Particles L-1), with a median size of ∼30 nm and an average mass of 0.13 fg, suggested relevant inorganic colloidal transport within the filtered fraction following the atmospheric deposition event. Geochemical signatures revealed persistent positive Cerium (Ce) Europium (Eu) anomalies of lithological origin. Although risk quotients (RQ) for the labile fraction decreased during the atmospheric deposition event due to low lability, the substantial increase in total REE burden suggests a transfer of ecological risk from the dissolved to the particulate phase. We conclude that conventional filtration overestimates REE bioavailability and that episodic atmospheric disturbances fundamentally alter the partitioning and fate of rare earth elements in freshwater systems.
Beauveria caledonica offers great potential as a biocontrol agent for certain pests and diseases. However, its ability to colonize plants as an endophyte and its interactions with pathogenic microorganisms within the plant are still not fully understood. In this study, we investigated the potential of B. caledonica isolated from banana weevils to colonize banana cultivar "Baxijiao" (Musa spp. AAA) and control the Tropical Race 4 (TR4) strain of Fusarium Wilt of Banana (Fusarium oxysporum f. sp. cubense (Foc). A four-point dual-culture confrontation test revealed that B. caledonica effectively inhibited the in vitro growth of Foc TR4, with an inhibition rate of 70.14%. Colonization experiments showed that B. caledonica could colonize the roots, corms, and pseudostems of banana plantlets. Finally, greenhouse experiments, arranged in a randomized complete block design, confirmed that B. caledonica could act as an endophyte, surviving inside the banana plant, and demonstrated that it significantly reduced Foc TR4 in the host plant, with an efficacy of 34.73%, without adversely affecting plant growth. This groundbreaking study confirms that an insect-pathogenic fungus, B. caledonica, isolated from banana weevils, can colonize banana plants and establish itself as an endophyte within host plants. Its demonstrated potential to antagonize Foc TR4 highlights its effectiveness as a biocontrol agent in banana production, which opens a new possibility for B. caledonica's dual roles in disease and pest management to be validated in large-scale field trials.
Exciton dissociation in semiconducting nanostructures is crucial for optoelectronic applications, especially when free-carrier generation is required. Despite considerable research, the question of whether and how such generation occurs in strongly excitonic systems remains elusive. Here, we use one-dimensional precision graphene nanoribbons (GNRs) as a model system to investigate exciton dissociation. We systematically explore the interplay between ribbon length (l), excitation energy, and band dispersion in various precision GNRs. Ultrafast Terahertz conductivity measurements reveal that hot exciton dissociation dominates carrier generation, with ribbon length significantly influencing free carrier lifetimes. We identify a critical Bjerrum length (RB) of approximately 20 nm that determines whether photoexcited hot carriers in GNRs can dissociate before forming tightly bound excitons. For shorter ribbons (l < 2RB), rapid ~ps exciton formation prevails. Furthermore, the charge-carrier band dispersion in GNRs plays a critical role in determining dissociation efficiency. Long GNRs with strongly dispersed bands, and consequently low effective carrier masses, exhibit higher mobilities that promote efficient hot-exciton dissociation. These results advance fundamental understanding of dimensionality, energetics, and electronic structure in excitonic materials, providing design principles for optoelectronic devices based on excitonic materials.
Previous studies using solvatochromic dyes as probes of diluted and succussed solutions have indicated that potencies produce an electric field and are also nullified by having a weak electric current passed through them. The objectives of the current study were to build and expand on these observations. In particular, it has been proposed that if potencies produce their own electric field, this is likely due to the presence of separated charges. On application of an electrical current these charges are predicted to recombine and in so doing emit light. A specially adapted single tube luminometer has been used to monitor photon emissions from potency solutions of Arsenicum album 10M (Ars 10M) and controls, using fluorescein to extend the detection range of the instrument. A sharp photon emission peak is detectable from solutions of Ars 10M on application of a 9v/18mA electric current. Potency solutions only show the peak on application of the electric current and control solutions show no peak. The presence of 10 µM fluorescein is necessary in order to see the emission peak. Calculations show the charge-pair concentration in solution is 10-14M, assuming one photon is emitted per charge-pair. For Ars 10M that has been subjected to an electric current, photon emission and loss of activity against the solvatochromic dye DMABR correlate. The sharp photon emission peak seen in solutions of Ars 10M, but not in control solutions, requires fluorescein to be present and indicates the photons emitted are in the ultraviolet range. The concentration of separate charge-pairs, calculated from the photon emission level, is approximately 10-14M. Their identity remains unknown at this time, but they appear to be responsible for the activity of Ars 10M, as determined by its action against DMABR, and by extrapolation its clinical activity.
Long-term potentiation (LTP) represents a fundamental form of synaptic plasticity that underlies long-term memory. Catecholaminergic projections from the locus coeruleus (LC) to the hippocampal CA1 region modulate spatial memory consolidation; however, it remains unclear whether activity in this pathway directly induces in vivo synaptic potentiation. The present study demonstrates that selective photostimulation of tyrosine hydroxylase-positive (TH+) LC axon terminals in CA1 induces robust optogenetic LTP (oLTP) in the Schaffer collateral pathway. Induction of oLTP is associated with increased extracellular concentrations of noradrenaline, dopamine, and glutamate in CA1, and is abolished by local blockade of β-adrenergic, D1 dopamine, or NMDA receptors. In awake, freely moving mice, post-training induction of oLTP enhances consolidation of weak object-location memories and promotes long-term persistence of spatial memory in the Morris water maze and Barnes maze for up to 10 days. These findings establish a causal relationship between LC-derived catecholaminergic input, in vivo hippocampal LTP induction, and durable spatial memory, and identify a circuit-specific neuromodulatory mechanism that regulates synaptic plasticity during memory consolidation.
Protein-protein interactions (PPIs) are fundamental to cellular processes, and essential for understanding biological function and disease mechanisms. In this review, we emphasize recent deep learning-based methods for protein interaction study. Focusing on three closely related tasks of proteome-wide PPI prediction, PPI interface prediction, and PPI co-complex structure prediction, we discuss how emerging concepts and computation approaches have evolved to shape these fields We categorize recent approaches according to their methodological paradigms, summarize their strengths and limitations, and further explore diverse biological and biomedical applications, highlighting how computational methods in PPI prediction, PPI interface prediction, and PPI structure prediction jointly contribute to understanding of complex biological systems.
Diabetic retinopathy (DR) is increasingly recognized not merely as a microvascular complication, but as a chronic neurodegenerative disorder of the central nervous system characterized by progressive neurovascular unit (NVU) dysregulation. In many individuals, DR continues to progress despite subsequent glycaemic normalization, a phenomenon known as metabolic memory. Emerging evidence indicates that transient hyperglycaemic stress is converted into durable transcriptional programs through epigenetic encoding mechanisms. In this Review, we propose a hierarchical framework in which early metabolic insults are written into chromatin via DNA methylation, histone modifications, and noncoding RNA networks. Crucially, these epigenetic storage systems do not act in isolation; they systematically disrupt the intricate intercellular crosstalk within the NVU. Epigenetic locking of microglia into pro-inflammatory phenotypes, coupled with Müller cell gliosis and the suppression of neural plasticity, drives sustained pathological shifts that transform localized cellular stress into a tissue-wide network collapse. Furthermore, we critically evaluate the potential of extracellular vesicle-mediated communication in amplifying this memory across the NVU. By targeting the fundamental epigenetic drivers of glial reactivity and neurodegeneration across the integrated NVU, this Review highlights innovative strategies, such as programmable epigenetic editing (CRISPR/dCas9), to reset homeostasis and offers a transformative paradigm for early intervention in DR.
The global rise in atmospheric CO2 concentration and its societal impact urges the development of sustainable carbon management via carbon capture, utilization, and storage (CCUS) strategies. Although CCUS addresses a challenge of global scale, the key processes occur at nanoscale interfaces among CO2, water, and solids, where reaction kinetics, thermodynamics, and transport determine CO2 fate and process performance, influencing the overall efficiency and sustainability of CCUS. Therefore, a better understanding and precise control of nanoscale interfacial chemistry in CCUS processes are vital. This review introduces the fundamental principles of CO2 interfacial reactions involved in CCUS, followed by a detailed examination of nanoscale interfacial processes in CO2 capture, utilization, and mineralization. We also explore the properties of various interfaces, the mechanisms governing nanoscale CO2 interactions, and their impacts on overall CCUS performance, highlighting how a deeper understanding and control of interfacial reactions can contribute to achieving net-zero CO2 emissions (NZE) targets. To support the characterization of these dynamic and complex interfacial processes, we discuss advanced characterization techniques for studying interfacial phenomena in carbon management systems. Finally, we suggest future research directions and opportunities in advancing carbon management by bridging nanoscale insights to field-scale applications of CCUS.
Mechanical stress is the most important factor affecting the progression of osteoarthritis (OA), but the mechanism linking mechanical stress to transcriptional repression remains elusive. Here, the study finds that mechanical stress induced epigenetic changes that can serve as therapeutic targets for osteoarthritis. By using Piezo1 conditional knockout (Col2a1CreERT; Piezo1flox/flox) mice, it was found that Piezo1 activation by excessive mechanical stress can trigger chromatin remodeling via cytoskeletal force transmission, promoting the histone demethylase Kdm5c-mediated epigenetic silencing. Kdm5c in turn erases H3K4me3 marks from promoters of cartilage-anabolic genes Col2a1 and Runx3, silencing their expression. Genetic ablation of Kdm5c rescues mechanical stress-induced cartilage degradation. Through drug repurposing, the study identifies telmisartan as a direct Kdm5c inhibitor that blocks this pathway and demonstrates disease-modifying efficacy in mouse OA models and human cartilage explants. These results establish the Piezo1-Kdm5c axis as a fundamental driver of OA and position telmisartan as a mechano-epigenetic therapy with immediate translational potential.