Browse Articles

Analysis of deep-resequencing data of 984 soybean accessions reveals structural variations underlying agronomic traits

Recoverable macroporous polyanion bead catalysts for scalable continuous chemical depolymerization of polyethylene terephthalate

Insights into the role of dopamine in rhizosphere microbiome assembly

Abstract Dopamine plays a critical role in animal physiology and interactions with gut microbes. In plants, dopamine is known to function in plant defense and abiotic stress tolerance; however, its role in mediating plant-microbiome interactions remains unexplored. In this study, we show that dopamine is one of the most abundant exometabolites with natural variation in root exudates across diverse Brachypodium distachyon lines, suggesting a potential role in rhizosphere microbial assembly. To further investigate this, we colonized ten natural B. distachyon lines with a 16-member bacterial synthetic community (SynCom), collected metabolomic and 16S rRNA sequencing data, and performed an association analysis. Our results reveal that dopamine levels in root exudates were significantly associated with the abundance of six SynCom members in a hydroponic system. In vitro growth studies demonstrated that dopamine had a significant effect on the growth of the same six bacterial isolates. Additionally, treating soil directly with dopamine enriched Actinobacteria, consistent with both the SynCom-dopamine correlations and the isolate growth results. Collectively, our study underscores the selective influence of dopamine on rhizosphere microbial communities, with implications for precision microbiome management.

Coupled and decoupled carbon-mercury dynamics across forest ecosystem continua

Improving flood detection with large-scale dashboard camera data

Abstract Flooding poses a significant and growing challenge globally, threatening infrastructure, livelihoods, and public safety. However, current methods for detecting floods are limited in their spatiotemporal granularity and inequitable in their coverage. Here, we propose BayFlood, a method for fine-grained urban flood detection that identifies flooded street scenes in large-scale dashboard camera datasets using a vision-language model. We leverage the ability of modern vision-language models to identify floods even without large labeled datasets, which are typically unavailable. We comprehensively validate our approach using 1,440,184 images, showing that our model provides strong signal for floods across multiple cities and time periods and that our flood detections correlate with known external predictors of flood risk. We show our approach can be used to improve flood detection in New York City: our analysis detects floods in neighborhoods overlooked by current methods, identifies demographic biases in existing methods, and suggests locations for new flood sensors. This work underscores the potential of leveraging dense street-level imagery to significantly improve the understanding, detection, and management of flooding, and is more broadly applicable to detecting other objects and incidents from street scene data even when no labeled data is available.

Transcriptomic profiling of human brown and white adipose tissue depots

Abstract Human adipose tissues are solid organs distributed throughout the body in specific locations and are thought to have dichotomous functions: white adipose tissue stores triglycerides as an energy reservoir, and brown adipose tissue uses metabolic fuels to generate heat. To define the transcriptional profile of six principal adipose depots, we analyze tissue from 11 autopsies (3 F/8 M, 16-71 y) of patients who had different underlying diseases. Despite global similarities in terms of cell type proportions, each depot has a distinct transcriptomic signature and functional profile. Each human’s adipose tissues are more similar to each other than to the anatomically and functionally matching depots in other patients. The transcriptomic pattern of subcutaneous white adipose tissue can even be used to predict the human donor. This pattern suggests that individualized factors such as genetics, age, environment, diet, and disease play impactful roles in coordinating the behavior of the whole-body adipose tissue depot.

Observation of discrete time quasicrystal in Rydberg atomic gases

Active conformations of neuronal Na+, K+-ATPase isoforms and a disease-causing mutant

A distinct CAR-T cell phenotype mediates therapeutic response at limited doses

Abstract Chimeric antigen receptor (CAR) T-cell therapies are typically administered at high doses to maximize durable clinical responses. However, manufacturing constraints can limit the production of sufficient cells to achieve the intended dose. Although some patients experience durable responses after receiving lower CAR-T cell doses, the mechanisms underlying efficacy at these limited cell numbers remain poorly understood. To address this, we performed deep phenotyping of anti-CD19 CAR-T cell products and their corresponding leukapheresis starting materials from a phase I/II dose-escalation trial. We also report the primary and secondary clinical outcomes of the diffuse large B-cell lymphoma, follicular lymphoma, and mantle cell lymphoma cohorts of the HD-CAR-1 basket trial (NCT03676504; EudraCT 2016-004808-60). Patients responding to low-dose CAR-T therapy showed dose-dependent enrichment of functional effector and effector memory-like CAR-T cells. The absolute number of these cells emerged as a robust biomarker of therapeutic response, valid across dose levels and CAR-T targets. Effective low-dose products were associated with high T-cell numbers and T-cell-supportive myeloid states in leukapheresis materials, whereas regulatory myeloid states promoted dysfunctional CAR-T cells and treatment failure. Our study provides insights into the phenotype, mechanisms, and biomarkers of CAR-T cells that drive therapeutic responses at low doses, with medical and socioeconomic implications.

A physics-informed eikonal model for simulating arrhythmias in the human heart in real-time

Abstract Personalized computational models of cardiac electrophysiology, referred to as cardiac digital twins, are considered a key technology for realizing precision cardiology by tailoring therapies to individual patients. However, the high computational demands of physically detailed simulations prohibit broader adoption of cardiac digital twins in practical applications. Here, we aim to address this challenge with a lightweight Physics-Informed Eikonal model that replicates the biophysical phenomena embedded within cardiac electrophysiology models along with clinical electrograms in near real-time, including arrhythmia scenarios. Validity of the proposed model is shown against a gold-standard cardiac electrophysiology model in complex arrhythmia simulations, including a scar-mediated ventricular tachycardia in a human whole-heart model. In this work, we show that the Physics-Informed Eikonal model delivers near-real time performance and retains high physical fidelity as required for the calibration of cardiac digital twins, thus providing a fundamental core technology to be leveraged in industrial and clinical applications.

Charting higher-order models of brain function beyond pairwise interactions

Casimir stabilization of fluctuating electronic nematic order

Abstract The field of vacuum cavity control of quantum materials aims to engineer quantum materials through electromagnetic zero-point fluctuations. In this work we articulate and theoretically study a generic mechanism for vacuum control of electronic order: Casimir control, where a fluctuating phase is stabilized by minimizing the zero-point energy of the surrounding electromagnetic continuum. We focus on the Casimir stabilization of fluctuating nematic order, where local order develops but thermal fluctuations inhibit long-range order. As a concrete example, we stabilize fluctuating quantum Hall stripes by leveraging the anisotropic electromagnetic environment of a birefringent crystal. We show that for experimentally feasible setups, an orientation-dependent Casimir energy emerges which can be 10 3 times larger than other known stabilization mechanisms, implying that our setting may be realized with currently available technology. We close by discussing connections to recent quantum Hall stripes experiments, as well as broader applications of Casimir control.

Frequency conversion of highly charged femtosecond spatiotemporal optical vortices in cascaded nonlinear crystals

Abstract The degrees of freedom inherent in spatiotemporal optical vortices (STOVs) afford intriguing opportunties to manipulate complex light fields for broad applications such as optical communication, light-matter interactions, particle manipulation, quantum optics, and electron acceleration in the relativistic regime. Unlike previous studies examining the second harmonic generation (SHG) of STOVs having an input topological charge (TC) $${l}^{\left(\omega \right)}=1$$ l ω = 1 at the fundamental frequency ω , here we experimentally demonstrate sequential second and third harmonic generation of STOVs to achieve greater spectral coverage, wavelength tunability, and what is more, TC values as great as $${l}^{\left(\omega \right)}=40$$ l ω = 40 . The large TC values are attributed to second (third) harmonic generation of an incident beam satisfying $${l}^{\left(2\omega \right)}=2{l}^{\left(\omega \right)}$$ l 2 ω = 2 l ω ( $${l}^{\left(3\omega \right)}=3{l}^{\left(\omega \right)}$$ l 3 ω = 3 l ω ). We found that wavelength tunability could be achieved by controlling the position of the phase singularity in the frequency domain while also optimizing the nonlinear phase matching condition. In this work, our experimental measurements extend the principle of conservation of the spatiotemporal topological charge to general nonlinear optical parametric processes, suggesting a fundamental approach to produce tunable and highly charged STOV deep into the ultraviolet regime.

The response regulator BqsR/CarR controls Fe2+ acquisition in Pseudomonas aeruginosa

Exciton thermal radiation from macroscale membranes composed of chirality-sorted carbon nanotubes and its control

Abstract Exciton thermal radiation, which can potentially be exploited for selective thermal emission and energy harvesting, has been observed in individual single-walled carbon nanotubes (SWCNTs) heated under photoirradiation. However, whether macroscale-SWCNT assemblies can emit exciton thermal radiation under thermal conduction heating remains unclear and constitutes an important challenge for practical applications. Herein, we observe peaked exciton thermal radiation from chirality-sorted SWCNT membranes. Transmission spectroscopy shows robust exciton resonance at high temperatures, resulting in clear exciton resonance in the thermal radiation band. The absolute emissivity spectra of the membranes are determined at 850 K. Exciton dominance suppresses the contribution of thermal free carriers to the infrared absorption/emission spectra, maintaining the transparency below the optical gap even at elevated temperatures. Furthermore, we demonstrate the enhancement of emissivity at the exciton resonance using a simple planar few-layer architecture consisting of alternating SWCNT and transparent dielectric layers, enabled by strong excitonic light-matter interactions in SWCNTs; this offers a pathway toward superior spectral selectivity at even higher temperatures. These results highlight the potential of chirality-sorted SWCNT membranes as a class of semiconductors for controlling thermal radiation at elevated temperatures, leveraging thermo-optical properties that differ from those of conventional bulk semiconductors.

Maternal hyperglycemia-induced O-GlcNAcylation of CaMKIIδ promotes mtDNA release and cardiac remodeling in offspring

Abstract Maternal diabetes during pregnancy increases the risk of metabolic and cardiac disorders in offspring. Nevertheless, the mechanism by which intrauterine hyperglycemia affects neonatal cardiac remodeling remains uncertain. This study aims to characterize the prenatal environment in the context of gestational diabetes mellitus and to identify the corresponding fetal changes. Using an intrauterine hyperglycemia rodent model, we observe cardiac remodeling and inflammatory responses in offspring hearts. Moreover, the O -GlcNAcylation levels are increased in neonatal hearts exposed to gestational diabetes. Further mechanistic investigations, supported by RNA sequencing and mitochondrial functional analyses, reveal that gestational diabetes triggers O -GlcNAcylation-dependent activation of CaMKIIδ during the embryonic stage. This activation leads to the release of mitochondrial DNA (mtDNA) from the mitochondrial matrix into the cytosol, which subsequently activates STING signaling and triggers an inflammatory response in neonatal cardiomyocytes. Pharmacological or genetic inhibition of O -GlcNAcylation attenuates mtDNA-induced myocardial inflammation and improves cardiac function in neonatal offspring subjected to intrauterine hyperglycemia. Together, these findings identify a previously unrecognized CaMKIIδ/mtDNA/STING axis in which CaMKIIδ O -GlcNAcylation leads to mtDNA-dependent activation of cardiac remodeling, suggesting that plasma mtDNA levels could serve as a predictive biomarker in neonatal cardiac inflammatory injury.

Wave morphing towards the flat-top envelope in photonics systems driven by artificial gauge fields

Abstract In quantum physics, classical optics, and many other wave systems, wave confinement in a finite domain leads to discrete eigenstates that typically exhibit spatially nonuniform, oscillatory profiles. A long-standing question is whether a confined system can counterintuitively support an eigenstate with a uniform, nonzero envelope, offering new opportunities for quantum emitters, optical antennas, and lasers. Here, we show that such a state can be realized through spatial phase engineering that acts as an artificial gauge potential. By continuously tuning the accumulated phase, the eigenvalue spectra undergo a spectral flow that reshapes the profiles of the eigenstates, enabling the formation of a flat-top state with a uniform yet nontrivial envelope. We implement this concept in a photonic crystal slab, where a central bulk region is surrounded by heterogeneous band gaps that tailor reflection phases to serve as an artificial local gauge field. By inducing single-mode lasing, we probe the morphing of mode envelope profiles, demonstrating a continuous transition from conventional oscillatory states to a flat-top state via near- and far-field measurements.

CO ₂ * Luminescence‐Navigated Oxide Overlayer Engineering for CO Oxidation

ABSTRACT Strong metal‐support interaction (SMSI)‐induced oxide overlayers critically govern the CO oxidation activity of metal‐supported catalysts. However, it remains challenging to predict the optimal oxide overlayer structure in CO oxidation due to its intertwined geometric and electronic effects. To address this, we introduce the luminescence of excited‐state CO 2 molecules (CO 2 *)‐ generated during their relaxation to the ground state in the CO oxidation reaction‐ as a novel “navigation gauge” for determining the ideal oxide overlayer on Au nanoparticles. The CO 2 * luminescence intensity in CO oxidation revealed a volcano‐shaped dependence on ZnO x overlayer coverage. More interestingly, such a volcano profile of the luminescence intensity directly aligned with the CO conversion tested in the fixed‐bed reactor, demonstrating a linear correlation between luminescence intensity and catalytic activity. Therefore, the CO 2 * luminescence served as an indicator for both the overlayer structure and the catalytic activity. Finally, the universality of the CO 2 * luminescence‐lighted strategy was validated over classical Au/MO x systems, including Au/TiO 2 ‐R (rutile), Au/TiO 2 ‐A (anatase), and Au/CeO 2 . It is anticipated that the CO 2 * luminescence‐lighted strategy not only lights up the intricate oxide overlayer structures but also provides a promising navigation tool for guiding the rational design of highly active CO oxidation catalysts, circumventing conventional trial‐and‐error optimization approaches.

High efficiency gold extraction by 2D metallic 1T/1T′ phase transition metal dichalcogenides

Unlocking High‐Rate Sodium Storage in Hard Carbon via Interfacial Conformation Entropy Modulation in Localized High‐Concentration Electrolytes

ABSTRACT Ether‐based electrolytes are extensively employed in sodium‐ion batteries (SIBs) featuring hard carbon (HC) anodes, owing to their favorable interfacial wettability and intrinsically low solvation energy. Nevertheless, conventional NaPF 6 ‐based systems are still hindered by limited initial Coulombic efficiency, suboptimal rate capability, and inadequate low‐temperature ion transport. Here, the concept of interfacial conformation entropy ( S ICE ) is introduced as a mechanistic descriptor to capture the reconfigurability of solvation sheath and its influence on Na + desolvation and interfacial migration. To validate this concept, a locally high‐concentration electrolyte (LHCE) is formulated by incorporating 10 vol% 1,4‐dioxane (14DX), a sterically hindered and weakly coordinating cyclic ether, into 1 M NaPF 6 in diethylene glycol dimethyl ether (DEGDME). This tailored solvation microenvironment enhances S ICE effectively, enabling solvent conformational flexibility that accelerates Na + desolvation and directs the formation of a highly conductive, mechanically robust interphase. Consequently, the HC|Na cell delivers ultrafast‐charging durability and maintains a reversible capacity of 154.28 mAh g −1 after 9000 cycles at 10C with a capacity retention as high as 89.46%. Simultaneously, an Ah‐level NVP|HC pouch cell further substantiates the practical viability of this strategy. These findings highlight S ICE as a powerful paradigm for the rational design of high‐rate SIB electrolytes.