The molecular hydrogen ions (MHI) are three-body systems suitable for advancing our knowledge in several domains: fundamental constants, tests of quantum physics, search for new interparticle forces, tests of the weak equivalence principle1 and, once the anti-molecule p¯p¯e+ becomes available, new tests of charge-parity-time-reversal invariance and local position invariance1-3. To achieve these goals, high-accuracy laser spectroscopy of several isotopologues, in particular H2+ , is required4. Here we present a Doppler-free laser spectroscopy of a H2+ rovibrational transition, achieving line resolutions as large as 2.2 × 1013. We accurately determine the transition frequency with 8 × 10-12 fractional uncertainty. We also determine the spin-rotation coupling coefficient with 0.1 kHz uncertainty and its value is consistent with the state-of-the-art theory prediction5. The combination of our theoretical and experimental H2+ data allows us to deduce a new value for the proton-electron mass ratio mp/me. It is in agreement with the value obtained from mass spectrometry and has 2.3 times lower uncertainty. From combined MHI, H/D and muonic H/D data, we determine the baryon mass ratio md/mp with 1.1 × 10-10 absolute uncertainty. The value agrees with the directly measured mass ratio6. Finally, we present a match between a theoretical prediction and an experimental result, with a fractional uncertainty of 8.1 × 10-12. Both results indicate a notable confirmation of the predictive power of quantum theory and the absence of beyond-the-standard-model effects at these levels.

Cross-scale coupling from magnetohydrodynamics (MHD) to non-MHD scales is important in interpreting observations of explosive events in nature, such as solar flares and geomagnetic storms1,2. Experiments and observations also link it to the emergence of energetic particles and X-rays3. However, how this multi-scale physics affects the abrupt onset of reconnection remains unknown. Here we report observations from laboratory experiments involving two flux ropes with electron beams that induce magnetic turbulence and then abruptly merge into a single structure, altering the magnetic topology in the MHD regime. Two separate electron beams are launched along magnetic field lines and form individual flux ropes with a drift velocity higher than the ambient Alfvén velocity, effectively driving magnetic turbulence through beam-driven instabilities, as inferred from the increased level of the turbulent power spectrum. Experimental observations, including the appearance of energetic particles, increased ion temperature and changes in the characteristics of the flux ropes, suggest that beam-driven turbulence drives three-dimensional (3D) reconnection. 3D particle-in-cell simulations are performed, which successfully reproduce the key aspects of the experiment. These results directly explain how non-MHD kinetic processes progress through multiple scales to induce global MHD changes.

Predicting the social and behavioural impact of future technologies before they are achieved would enable us to guide their development and regulation before these impacts get entrenched. Traditionally, this prediction has relied on qualitative, narrative methods. Here we describe a method that uses experimental methods to simulate future technologies and collect quantitative measures of the attitudes and behaviours of participants assigned to controlled variations of the future. We call this method 'science fiction science'. We suggest that the reason that this method has not been fully embraced yet, despite its potential benefits, is that experimental scientists may be reluctant to engage in work that faces such serious validity threats. To address these threats, we consider possible constraints on the types of technology that science fiction science may study, as well as the unconventional, immersive methods that it may require. We seek to provide perspective on the reasons why this method has been marginalized for so long, the benefits it would bring if it could be built on strong yet unusual methods, and how we can normalize these methods to help the diverse community of science fiction scientists to engage in a virtuous cycle of validity improvement.

Data-driven methodologies have transformed the discovery and prediction of hard materials with well-defined atomic structures by leveraging standardized datasets, enabling accurate property predictions and facilitating efficient exploration of design spaces1-3. However, their application to soft materials remains challenging because of complex, multiscale structure-property relationships4-6. Here we present a data-driven approach that integrates data mining, experimentation and machine learning to design high-performance adhesive hydrogels from scratch, tailored for demanding underwater environments. By leveraging protein databases, we developed a descriptor strategy to statistically replicate protein sequence patterns in polymer strands by ideal random copolymerization, enabling targeted hydrogel design and dataset construction. Using machine learning, we optimized hydrogel formulations from an initial dataset of 180 bioinspired hydrogels, achieving remarkable improvements in adhesive strength, with a maximum value exceeding 1 MPa. These super-adhesive hydrogels hold immense potential across diverse applications, from biomedical engineering to deep-sea exploration, marking a notable advancement in data-driven innovation for soft materials.

There is ongoing debate about the vulnerability of arthropods to climate change1,2. Long-term impacts of climate change on arthropod communities could manifest through short-term weather patterns3. Arthropods in the tropics are hyper-diverse4,5 and contribute many crucial ecosystem functions6,7, but are comparatively less studied than in temperate regions1,8,9. Tropical forest arthropods and the functions that they provide may be vulnerable to intensified El Niño events under climate change10-12. Here we perform time-series analysis of data from primary tropical forests, which reveal long-term declines in arthropod diversity and function that were linked to El Niño occurrence. In the Americas, species losses correlated with El Niño sensitivity, and abundant species fluctuated according to feeding traits and level of ecological specialization. Parallel declines in butterflies in Southeast Asia suggested that impacts spanned continents. Predicted arthropod diversity changes correlated with observed rates of invertebrate-mediated decomposition and leaf herbivory, which were oscillating and crashing, respectively, across the tropics. Our analyses suggest that an intensified El Niño immediately threatens tropical forest arthropods and the ecosystem functions that they provide. The broader consequences remain unknown, but such widespread changes could fundamentally alter tropical forest ecosystems13. Long-term monitoring of arthropod diversity and forest functioning across the tropics is paramount, as is researching the potential mechanisms that underly this novel threat.

Glycosylation is central to the localization and function of biomolecules1. We recently discovered that small RNAs undergo N-glycosylation2 at the modified RNA base 3-(3-amino-3-carboxypropyl) uridine (acp3U)3. However, the functional significance of N-glycosylation of RNAs is unknown. Here we show that the N-glycans on glycoRNAs prevent innate immune sensing of endogenous small RNAs. We found that de-N-glycosylation of cell-culture-derived and circulating human and mouse glycoRNA elicited potent inflammatory responses including the production of type I interferons in a Toll-like receptor 3- and Toll-like receptor 7-dependent manner. Furthermore, we show that N-glycans on cell surface RNAs prevent apoptotic cells from triggering endosomal RNA sensors in efferocytes, thus facilitating the non-inflammatory clearance of dead cells. Mechanistically, N-glycans conceal the hypermodified uracil base acp3U, which we identified as immunostimulatory when exposed in RNA. Consistent with this, genetic deletion of an enzyme (DTWD2) that synthesizes acp3U abrogated innate immune activation by de-N-glycosylated small RNAs and apoptotic cells. Furthermore, synthetic acp3U-containing RNAs are sufficient to trigger innate immune responses. Thus, our study has uncovered a natural mechanism by which N-glycans block RNAs from inducing acp3U-dependent innate immune activation, demonstrating how glycoRNAs exist on the cell surface and in the endosomal network without inducing autoinflammatory responses.

Tunability in active metasurfaces has mainly relied on shifting the resonance wavelength1,2 or increasing material losses3,4 to spectrally detune or quench resonant modes, respectively. However, both methods face fundamental limitations, such as a limited Q factor and near-field enhancement control and the inability to achieve resonance on-off switching by completely coupling and decoupling the mode from the far field. Here we demonstrate temporal symmetry breaking in metasurfaces through ultrafast optical pumping, providing an experimental realization of radiative-loss-driven resonance tuning, allowing resonance creation, annihilation, broadening and sharpening. To enable this temporal control, we introduce restored symmetry-protected bound states in the continuum. Even though their unit cells are geometrically asymmetric, coupling to the radiation continuum remains fully suppressed, which, in this work, is achieved by two equally strong antisymmetric dipoles. By using selective Mie-resonant pumping in parts of these unit cells, we can modify their dipole balance to create or annihilate resonances as well as tune the linewidth, amplitude and near-field enhancement, leading to potential applications in optical and quantum communications, time crystals and photonic circuits.

Despite significant advances in microbiome research across various environments1, the microbiome of Earth's largest biomass reservoir-the wood of living trees2-remains largely unexplored. Here, we illuminate the microbiome inhabiting and adapted to wood and further specialized to individual host tree species, revealing that wood is a harbour of biodiversity and potential key players in tree health and forest ecosystem functions. We demonstrate that a single tree hosts approximately one trillion bacteria in its woody tissues, with microbial communities distinctly partitioned between heartwood and sapwood, each maintaining unique microbiomes with minimal similarity to other plant tissues or ecosystem components. The heartwood microbiome emerges as a particularly unique ecological niche, distinguished by specialized archaea and anaerobic bacteria driving consequential biogeochemical processes. Our findings support the concept of plants as 'holobionts'3,4-integrated ecological units of host and associated microorganisms-with implications for tree health, disease and functionality. By characterizing the composition, structure and functions of tree internal microbiomes, our work opens up pathways for understanding tree physiology and forest ecology and establishes a new frontier in environmental microbiology.

Exoplanets are organized in a broad array of orbital configurations1,2 that reflect their formation along with billions of years of dynamical processing through gravitational interactions3. This history is encoded in the angular momentum architecture of planetary systems-the relation between the rotational properties of the central star and the orbital geometry of planets. A primary observable is the alignment (or misalignment) between the rotational axis of the star and the orbital plane of its planets, known as stellar obliquity. Hundreds of spin-orbit constraints have been measured for giant planets close to their host stars4, many of which have revealed planets on misaligned orbits. A leading question that has emerged is whether stellar obliquity originates primarily from gravitational interactions with other planets or distant stars in the same system, or if it is 'primordial'-imprinted during the star-formation process. Here we present a comprehensive assessment of primordial obliquities between the spin axes of young, isolated Sun-like stars and the orientation of the outer regions of their protoplanetary disks. Most systems are consistent with angular momentum alignment but about one-third of isolated young systems exhibit primordial misalignment. This suggests that some obliquities identified in planetary systems at older ages-including the Sun's modest misalignment with planets in the Solar System-could originate from initial conditions of their formation.