Spinal interbody fusion cages must be able to bear heavy loads while integrating seamlessly with the surrounding bone. However, the cages currently used in spinal surgery often fall short on both fronts. To meet the multi-faceted requirements, here, we introduce, for the first time, additively manufactured, biodegradable Zn-Mg interbody fusion cages with multi-scale structural control, combining eutectic microstructure, heterogeneous grain architecture, and gyroid lattices reinforced by interpenetrating ribs. The resulting cages showed a compressive strength comparable to that of cortical bone, together with good ductility and low elastic modulus. In vitro, balanced release of Zn²⁺ and Mg²⁺ enhanced osteogenic differentiation while mitigating Zn²⁺ toxicity. Zn-Mg extracts effectively alleviated the negative effects of estrogen deficiency on osteoblasts and osteoclasts. In an anterior cervical discectomy and fusion (ACDF) sheep model, the Zn-Mg cages exhibited excellent biocompatibility, rapid osseointegration, and robust mechanical interlocking, and maintained intervertebral stability during in vivo degradation for 24 weeks. The AM Zn-Mg cages through dual biomechanical-biological optimization are demonstrated to be a transformative alternative to current permanent metallic and polymeric implants in spinal fusion.

Distributed energy resources (DERs) are transforming power networks, challenging traditional operational methods, and requiring new coordination mechanisms. To address this challenge, this paper introduces SecuLEx (Secure Limit Exchange), a market-based paradigm for allocating and trading power injection and withdrawal limits, known as dynamic operating envelopes (DOEs). Under this paradigm, distribution system operators (DSOs) first assign initial DOEs to customers through a fair allocation mechanism. These limits can be exchanged afterward through a market, allowing customers to reallocate them according to their needs while ensuring network operational constraints. We formalize SecuLEx and illustrate DOE allocation and market exchanges on a small-scale low-voltage (LV) network. In this case study, SecuLEx reduces renewable curtailment and improves grid utilization and social welfare compared to traditional approaches.

Uncertainty fundamentally shapes human perception and decision-making, a factor that is becoming increasingly critical as autonomous vehicles (AVs) begin to share physical and social spaces with humans. This perspective paper synthesizes insights from neuroscience, robotics, and behavioral science represent uncertainty and act under it. We identify a significant disconnect between low-level mathematical concepts of uncertainty and risk, the uncertainty-aware prediction and planning methods used in robotics, and the high-level psychological uncertainty experienced by humans. Here, we conceptualize an integration pathway for mixed-mode mobility: we show that all three treat control under partial information as the same two-stage problem – probabilistic inference of the current and future state, followed by a risk -weighted choice of action – and we make this shared structure explicit. We thus argue that AVs should quantify and calibrate their own uncertainty, select risk metrics that reflect both individual and collective safety, model how their actions shape human uncertainty and behavior, and communicate intent and confidence in ways that support predictable interaction. This synthesis positions psychological uncertainty as a behaviorally relevant variable for AV design and outlines a research agenda for safer, more understandable transport systems.

This multi-site experimental study investigated the Hue-Heat Hypothesis (HHH), which posits that light hues can influence human thermal perception, as well as broader cross-modal interactions between visual and thermal domains. Across 464 experimental sessions in eight test rooms around the world, participants were exposed to varied thermal conditions (∼20 °C, ∼24 °C, ∼26 °C, and ∼28 °C) and typical white-light Correlated Color Temperatures (CCT, warm light: ∼3000 K; neutral: ∼4000 K; cool light: ∼6000 K) from LED sources (horizontal illuminance: ∼500 lx). The study assessed thermal, visual, and overall perceptions. Results revealed that thermal sensation and preference were predominantly influenced by thermal conditions, gender, and the laboratory setting, indicating that no statistically significant effects were found in support of the HHH. Similarly, visual perceptions were influenced by lighting conditions but not by the thermal environment. For instance, cool light was perceived as brighter than warm light, leading participants to prefer brighter light under warm light hues. Ultimately, this research revealed the significant challenges of interlaboratory experiments in this field, as local climate and test-room characteristics complicate both the conduct and the standardization of data analysis. Our findings highlight both the limited role of white-light CCT in shaping thermal sensations and the methodological challenges of multi-site comfort research, underscoring the need for careful data harmonization and context-aware analyses in future international collaborations.

Phosphorylation, a crucial post-translational modification (PTM), plays a central role in cellular signaling and disease mechanisms. Mass spectrometry-based phosphoproteomics is widely used for system-wide characterization of phosphorylation events. However, traditional methods struggle with accurate phosphorylated site localization, complex search spaces, and detecting sequences outside the reference database. Advances in de novo peptide sequencing offer opportunities to address these limitations, but have yet to become integrated and adapted for phosphoproteomics datasets. Here, we present InstaNovo-P, a phosphorylation specific version of our transformer-based InstaNovo model, fine-tuned on extensive phosphoproteomics datasets. InstaNovo-P surpasses existing methods in phosphorylated peptide detection and phosphorylated site localization accuracy across multiple datasets, including complex experimental scenarios. Our model robustly identifies peptides with single and multiple phosphorylated sites, effectively localizing phosphorylation events on serine, threonine, and tyrosine residues. We experimentally validate our model predictions by studying FGFR2 signaling, further demonstrating that InstaNovo-P uncovers phosphorylated sites previously missed by traditional database searches. These predictions align with critical biological processes, confirming the model’s capacity to yield valuable biological insights. InstaNovo-P adds value to phosphoproteomics experiments by effectively identifying biologically relevant phosphorylation events without prior information, providing a powerful analytical tool for the dissection of signaling pathways.

Acidophilic and metallotolerant microalgae represent an indispensable element of strategies to exploit or revive acid mine drainage ponds and similar systems with high levels of dissolved metal ions. The selection of an optimal strain for a specific application depends on the capacity to tolerate selected metal(s) and on the mechanisms of tolerance. Herein we examined the tolerance to manganese by Chlamydomonas acidophila PM01, an extremophilic strain that lives under acidic conditions and high concentrations of iron and other metals in its anthropogenic aquatic habitat. PM01 survived an extremely high Mn concentration of 50 mM (2.75 g/L). At 20 mM, cells kept intracellular Mn concentrations at a low level probably through binding to the cell wall, and vacuolization and excretion of Mn from the cell. Mn²⁺ was sequestrated by oxygen ligands, including phosphates, in octahedral geometry, in vacuoles and the cell wall. Energy challenges induced by Mn excess are met by the consumption of starch and lipid reserves, and improved photosynthetic performance. The exposure to Mn excess was related to decreased abundance of Fe-metalloenzymes and mild oxidative stress. The tolerance to Fe is coincident to tolerance to Mn. Acidophilic microalgae may be used for commercialization of metal-infested waters through biomass and biofuels production avoiding the need to use freshwaters and reducing contamination by other organisms. Finally, our study points out a novel low-intracellular Mn retention tolerance model that may be specific to acidophilic eukaryotic microalgae and enable superior survival tolerance. However, such strategy of tolerance is not optimal for bioremediation.

Driving infrared (IR)-active phonons to large amplitudes to enable non-equilibrium crystal lattice distortions, known as non-linear phononics, can initiate phase transitions along non-thermal pathways, providing transient control of various material properties beyond the equilibrium limits. Yet, how these non-thermal lattice-driven states evolve and thermalize remains unresolved. Here, we explore the crossover from non-thermal to thermal magnetization dynamics in dysprosium orthoferrite (DyFeO₃), driven by the resonant excitation of IR-active phonons. Using mid-infrared light pulses, we induce a transition from the collinear antiferromagnetic to the weakly ferromagnetic (WFM) phase, resulting in the emergence of net magnetization. Time-resolved single-shot magneto-optical imaging across multiple timescales reveals two distinct regimes. First, magnetization emerges as a spatially uniform state whose direction is controlled by the pump polarization, indicative of a non-thermal mechanism driven by non-linear phononics. On longer timescales, this state relaxes into a multidomain pattern that is insensitive to the pump polarization, consistent with thermal equilibration. The crossover occurs on a timescale of about 200 ps, far exceeding the IR phonon coherence time and consistent with the spin-lattice relaxation time in the WFM phase. These findings provide direct temporal and spatial fingerprints of non-linear-phononics-driven magnetic phase control, defining intrinsic limits for reversible ultrafast manipulation of magnetic order.

Duchenne muscular dystrophy (DMD) causes progressive muscle degeneration due to dystrophin deficiency. Dystrophin is also expressed in the brain during development and postnatally, yet a characterization of dystrophin isoform expression across brain cells and regions is lacking, limiting our understanding of the cognitive impairment affecting one-third of the patients and hampering the development of dystrophin-restoring drugs in the central nervous system (CNS). Here, we applied spatial transcriptomics to map Dmd isoforms across mouse brain regions and cell types. Mdx52 mice received exon 51-skipping therapies restoring the Dp427-sized isoform at the transcript and protein levels. We observed distinct spatial patterns: full-length isoforms localized to deeper cortical layers and CA1, while shorter isoforms were enriched in cortical layer 1 and dentate gyrus. We present evidence of isoform restoration, immune activation following treatment, and a framework to evaluate exon-skipping therapies in the CNS using spatial transcriptomics.

The Jupiter and Icy Moons Explorer (JUICE) mission of the European Space Agency (ESA) will investigate the Jovian system with multiple instruments over several years, beginning in early 2031. This paper describes the historical context and state of knowledge, as well as JUICE’s scientific goals and measurement techniques of the satellites that will not be encountered in close flybys. These include the large volcanically active moon Io, the four small inner moons Metis, Adrastea, Amalthea, and Thebe, and the numerous small Irregular (outer) moons. JUICE will provide multiple opportunities to observe Io from relatively remote distances of hundreds of thousands of kilometers. These observations will enable monitoring of Io’s surface for changes, and for the study of its neutral clouds and plasma torus. Io observations will be performed with the four optical remote sensing instruments and with the Particle Environment Package. For the small inner moons it is planned to obtain complete geographic longitude (scales up to 8 km/px), solar-phase and multi-color coverage, oblique polar views, and UV to near-IR spectra. Astrometric measurements will also be performed. The Irregular moons will mostly appear unresolved to the JUICE instruments. Nonetheless, long-duration disk-integrated lightcurves will be acquired to derive rotation periods, object dimensions, pole-axis orientations, and colors for most objects for the first time. From these data, convex-shape models will be generated and phase curves determined. Furthermore, the precision of the orbital elements will be improved via accurate astrometry. UV and near-IR measurements will be attempted for the largest of these objects.

In antiferromagnets, where quantum mechanical exchange interactions dictate spin behaviour, understanding the dynamics of magnons—collective spin wave excitations that naturally reach terahertz frequencies and supersonic velocities—is essential for both fundamental science and emerging technologies. Femtosecond optical pulses offer a powerful means to coherently excite these magnons across the full Brillouin zone and to manipulate their spectral characteristics. Yet, achieving such control has remained difficult, as it requires ultrafast and sustained tuning of the underlying exchange interaction. Here we demonstrate an optically driven renormalization of the terahertz magnon spectrum in the insulating antiferromagnet DyFeO₃. Our results show that this transformation arises from a substantial transient reduction of the exchange interaction within a nanoscale region near the surface. These findings reveal a route to light-induced, nanoscale control of antiferromagnetic spin dynamics, opening opportunities for reconfigurable, ultrafast magnonic and spintronic functionalities.

The monolithic integration of perovskite top cells on textured crystalline silicon affords efficient tandem devices with strong prospects for large-scale applications. Such integration has primarily relied on state-of-the-art recombination junctions, which typically comprise transparent conductive oxides and molecular self-assembled monolayer (SAM) contacts. However, the potential influence of bottom cell nanoroughness, which may vary based on specific processing routes and technologies, has received far less attention. Here, we systematically engineered the top surface nanoroughness of silicon heterojunction solar cells to examine its impact on monolithic perovskite–silicon tandem solar cells. We employed two approaches: (i) varying the thickness of (n)-type hydrogenated nanocrystalline silicon ((n)nc-Si:H) layers or (ii) applying a plasma treatment using a hydrogen and carbon dioxide gas mixture before the deposition of (n)nc-Si:H layers. Both methods enhanced the conductivity and crystallinity of (n)nc-Si:H layers and increased the surface nanoroughness, with plasma treatment enabling the efficient realization of distinct nanoroughness in thin (n)nc-Si:H (15-nm-thick) layers. Our results reveal that the surface nanoroughness imposed by (n)nc-Si:H layers influences the SAM anchoring, leading to increased work function shifts and improved SAM/perovskite interface quality, thereby impacting the overall tandem device performance. Notably, tandem devices incorporating higher-nanoroughness bottom cells achieved increased fill factors, dominating the observed tandem efficiency enhancements, with a peak efficiency of 32.6% enabled by a 30-second-long plasma treatment.

(Invasive) electrophysiology and magnetic resonance imaging (MRI) are central to the presurgical evaluation of patients with focal drug-resistant epilepsy (DRE), providing complementary but incomplete views of the epileptogenic zone (EZ). Although numerous studies combine these modalities, a comprehensive overview of how electrophysiology and MRI can be systematically integrated across MRI modalities is currently lacking. This narrative review synthesizes state-of-the-art methods for integrating electrophysiology with MRI in epilepsy research. Rather than focusing solely on spatial overlap or comparative performance, we highlight approaches in which each modality informs the other. We outline key principles, advantages, and limitations of existing strategies, discuss epilepsy-specific and multimodal integration challenges, and describe methodological directions to address them. Importantly, despite the breadth of proposed approaches, only a small number of integration strategies are currently used in routine clinical practice, whereas many others remain confined to the research domain. We consider emerging opportunities and remaining barriers for clinical translation toward improved localization of the EZ and better prediction of surgical outcomes.