Browse Articles

Activation entropy of dislocation glide in body-centered cubic metals from atomistic simulations

Publisher Correction: Optimal active unsupervised fault detection in cascaded h-bridge inverters based on machine learning

The future of universities: a Nature special report

Plasmon-Induced Ultrafast Interfacial Charge Transfer for Enhanced Photocatalytic Hydrogen Evolution

Kinetic selectivity in metal-organic framework chemical sensors

Novel sandwich structure of electrospun PLA calixarene nanofiber membranes for improved heavy metal ion removal performance

A Bifunctional Chiral Disulfide Catalyst for Highly Enantioselective Anti-Markovnikov Hydrophosphinylation

An active bifunctional natural dye for stable all-solid-state organic batteries

Insights in nonlinear ground response in volcanic environments from distributed dynamic strain sensing

Abstract Volcanic environments are often characterized by frequent explosive activity and complex ground features. Explosions can couple into the ground, triggering ground response (GR) influenced by near-surface properties. While GR resulting from seismic input is well-studied, GR generated by air-to-ground coupling of volcanic explosions remains poorly understood. Investigating this phenomenon is crucial for understanding near-surface material dynamics and improving volcanic hazard assessments. To study explosion-induced GR, a multi-parametric network was deployed near Mt. Etna’s summit craters in 2019, where GR had been previously observed. The network includes broadband seismometers, infrasound sensors, and a fibre optic cable for distributed dynamic strain sensing (DDSS). Over 65,000 explosions were recorded, with some triggering high-frequency GR signals (10–50 Hz) in the DDSS data. These high-frequency signals, embedded in low-frequency explosions (0.7–4 Hz), amplify upon coupling into the ground. We also classified the explosions using waveform similarity, and GR signals were analysed using an adapted approach incorporating temporal and spatial dimensions. Strain rate vs. pressure rate relationships derived from classified signals were interpreted in terms of either linear elastic or hyperelastic near-surface behaviour. Despite no clear consensus towards which mechanical model describes best the ground behaviour, we suggest a nonlinear site amplification driven by mechanical particle interactions rather than near-surface layer resonance.

Water Adsorption in Metal–Organic Frameworks: Characteristics, Mechanisms, and Structure–Property Relationships

A foundation model for human-AI collaboration in medical literature mining

Abstract Applying artificial intelligence (AI) for systematic literature review holds great potential for enhancing evidence-based medicine, yet has been limited by insufficient training and evaluation. Here, we present LEADS, an AI foundation model trained on 633,759 samples curated from 21,335 systematic reviews, 453,625 clinical trial publications, and 27,015 clinical trial registries. In experiments, LEADS demonstrates consistent improvements over four cutting-edge large language models (LLMs) on six literature mining tasks, e.g., study search, screening, and data extraction. We conduct a user study with 16 clinicians and researchers from 14 institutions to assess the utility of LEADS integrated into the expert workflow. In study selection, experts using LEADS achieve 0.81 recall vs. 0.78 without, saving 20.8% time. For data extraction, accuracy reached 0.85 vs. 0.80, with 26.9% time savings. These findings encourage future work on leveraging high-quality domain data to build specialized LLMs that outperform generic models and enhance expert productivity in literature mining.

The dynamic states of hepatitis B virus capsid monomers under the impact of different class of capsid-assembly modulators

An Activatable and Covalent Tumor-Associated Antigen Capturer Enabling Systemic Injection <i>In Vivo</i> for Promoted Antitumor Immunity

An integrated multi-omic natural history study of human development, sexual dimorphism, and the effects of trisomy 21

Kinetics of adrenomedullin pathway activation in a porcine sepsis model and a human cohort of sepsis and septic shock

Abstract Sepsis is a life-threatening condition characterized by endothelial dysfunction. The peptide hormone adrenomedullin (ADM) plays a key role in sepsis owing to its potent vasodilatory effects, ability to maintain vascular integrity, and critical role in modulating immune responses and reducing inflammation. To gain its biological activity, the inactive ADM precursor (ADM-Gly) is converted into its active form (bio-ADM) by peptidylglycine α-amidating monooxygenase (PAM). Here, we present hourly resolved kinetics of ADM activation during early sepsis onset in a porcine model and analyze the AdrenOSS-1 human cohort data to assess biomarker changes in advanced sepsis progression. The porcine model data showed that both bio-ADM and ADM-Gly mean concentrations rose within the first two hours post-induction, preceding measurable sepsis onset, with a greater increase in ADM-Gly (260.8 ± 92.0 pg/mL) compared to bio-ADM (28.0 ± 12.9 pg/mL). PAM activity increased at 6 h (39.3 ± 10.5 Units), accompanied by a rise in the bio-ADM/ADM-Gly ratio. AdrenOSS-1 study revealed that ICU sepsis patients had higher ADM-Gly (121.5 pg/mL [IQR: 44.4–284.1]) and PAM activity (23.5 Units [IQR: 17.7–32.7]) than controls. Elevated ADM-Gly (&gt; 730 pg/mL) and PAM activity (&gt; 35.1 Units) were associated with increased 28-day mortality, with non-survivors exhibiting higher ADM-Gly (603.5 pg/mL [IQR: 131.1–1443]) and PAM activity (28.3 Units [IQR: 19.0–45.1]) than survivors. This study provides novel insights into the dynamics of adrenomedullin (ADM) homeostasis during sepsis progression, highlighting the critical interplay between its glycine-extended precursor (ADM-Gly), fully active form (bio-ADM), and the amidating enzyme PAM. The findings demonstrate that early and significant elevations in ADM-Gly, accompanied by delayed PAM activity, result in incomplete ADM amidation, compromising endothelial barrier function. Elevated ADM-Gly and PAM activity were associated with increased sepsis severity and 28-day mortality, while a higher bio-ADM/ADM-Gly ratio was linked to improved survival. These results underscore the potential of ADM-Gly, bio-ADM, and PAM as biomarkers for sepsis severity and prognosis, and support therapeutic strategies aimed at enhancing PAM activity to restore endothelial integrity and improve patient outcomes in sepsis.

Catalytic Asymmetric (<i>ene</i>–<i>endo</i>)-Carbonyl–Ene Type Cyclizations

Giant Spin-flop magnetoresistance in a collinear antiferromagnetic tunnel junction

Content validity of the Mental Health Literacy Scale for perinatal use based on expert and patient input

Ultrastable Copper Cluster Enables Highly Site-Selective and Chemoselective Carbocation C(sp³)–H and C(sp²)–H Bonds Functionalization

Unifying frequency metrology across microwave, optical, and free-electron domains

Abstract Frequency metrology lies at the heart of precision measurement. Optical frequency combs provide a coherent link uniting the microwave and optical domains in the electromagnetic spectrum, with profound implications in timekeeping, sensing and spectroscopy, fundamental physics tests, exoplanet searches, and light detection and ranging. Here, we extend this frequency link to free electrons by coherent modulation of the electron phase by a continuous-wave laser locked to a fully stabilized optical frequency comb. Microwave frequency standards are transferred to the optical domain via the frequency comb, and are further imprinted in the electron spectrum by optically modulating the electron phase with a photonic chip-based microresonator. As a proof-of-concept demonstration, we apply this frequency link in the calibration of an electron spectrometer and verify its precision by measuring the absolute optical frequency. This approach achieves a 20-fold improvement in the accuracy of electron spectroscopy, relevant for investigating low-energy excitations in quantum materials, two-dimensional materials, nanophotonics, and quantum optics. Our work bridges frequency domains differed by a factor of  ~ 1013 and carried by different physical objects, establishes a spectroscopic connection between electromagnetic waves and free-electron matter waves, and has direct ramifications in ultrahigh-precision electron spectroscopy.