The 'excess oxygen' stored in deep Earth magma may help explain how Earth’s atmosphere became oxygen-rich
Peer-Reviewed Publication
Updates every hour. Last Updated: 20-Oct-2026 14:16 ET (20-Oct-2026 18:16 GMT/UTC)
A recent study published in National Science Review has revealed silicate magma can store far more oxygen than its chemically allows. In high-pressure experiments, silicate melt can store up to about 5 wt.% excess oxygen, which is released as the magma rising. The findings suggest that oxygen-rich magmas could carry oxidizing power from Earth’s interior toward the surface, and may explain links between large-scale magmatism episodes and atmospheric oxidation in Earth’s history.
Aerogel fibers have been considered as a promising solution for thermal protection textiles due to their high porosity and low thermal conductivity. However, the scalable production of sustainable and mechanical strong aerogel fibers remains a critical challenge. Here, inspired by the porous core–shell structure of polar bear hair, we report a continuous strategy to fabricate all-biomass aerogel fibers featuring an encapsulated core–shell architecture using silk fibroin as the core and cellulose as the shell. This tunable structure, with radially aligned sheet-like pores and adjustable shell thickness, is achieved through hydrogen bond-driven cellulose contraction and alcohol-induced curing of sheet-like silk fibroin. Such a porous architecture effectively suppresses convective heat transfer and promotes a multi-reflective effect for infrared radiation. The resulting fibers exhibit good mechanical robustness with a tensile load of a single aerogel fiber is up to 200 g without reinforcement. Meanwhile, the aerogel fiber maintains high porosity (79.78%), low thermal conductivity (52.4 ± 4.2 mW m−1 K−1), and low density (0.193 ± 0.01 g cm−3). Furthermore, an aerogel glove fabricated from these fibers demonstrates good thermal insulation. These results provide new insights for the design of biomimetic aerogel fibers with core–shell architecture, offering a scalable and eco-friendly pathway toward advanced wearable thermal management.
The aqueous zinc metal batteries (AZMBs) are famous for high-safety and high-energy-density, but limited by severe challenges around the Helmholtz plane layer such as the strong ion–dipole interactions between Zn2+ and H2O, resulting in slow desolvation processes and limited transport kinetics as well as corresponding higher barriers. To reconstruct the ion–dipole surroundings, the interface chemistry of employing a high permanent dipole moment of L-Carnosine (L-CN) has been proposed, weakening the interactions between Zn2+ and H2O to realize a crowded Zn2+-conductive structure, accelerating the desolvation kinetics. As revealed, the strong affinity between L-CN and Zn2+ enables the L-CN molecules to repulse H2O, reconfiguring the inner Helmholtz plane layer, thereby inhibiting the active water molecular to form hydrogen evolution reactions. Consequently, the Zn//Zn symmetric cells with Helmholtz plane modulation achieve a long lifespan up to 7000 h, a high Coulombic efficiency of 99.72%, and a high stabilization at high depth of discharge (85.4%). The assembled Zn//V2O5−x full cell with optimal electrolyte delivers the capacity of 289 mAh g−1 after 500 cycles at 1 A g−1 under an N/P ratio of 3.98. Impressively, the large-scale pouch cell with optimal electrolyte stabilizes for 200 cycles, offering the bright future of reconstructing Helmholtz plane for achieving high-performance AZMBs.
Researchers have developed a novel composite hydrogel film that combines a polyacrylamide and calcium alginate polymer network with in-situ calcium carbonate mineralization. This innovative approach provides a new structural method for regulating film swelling and enabling the controlled release of phycocyanin, a bioactive pigment-protein complex known for its antioxidant and antibacterial properties. The findings, recently published by Frontiers of Materials Science, open promising avenues for advanced biomedical applications, including wound dressings and tissue engineering.
Using a two-sample Mendelian randomization approach, this study (1349 cases, 203,231 controls from the FinnGen study) examined causal associations between 16 lifestyle behaviors and potential risk factors and blepharoptosis. Genetically predicted leisure screen time was associated with higher odds of blepharoptosis, with indicative evidence for BMI and current smoking as risk factors and physical activity and smoking cessation as protective factors.
This structured narrative review synthesizes evidence from randomized controlled trials, prospective studies, retrospective multicentric cohorts, and real-world investigations evaluating low-dose atropine (≤0.05%) for myopia control in Indian children. Indian studies consistently show that 0.01% atropine reduces myopia progression by approximately 50%–65% with minimal adverse effects, while 0.05% atropine offers greater efficacy with slightly more mild ocular side effects, consistent with international trials such as ATOM and LAMP.
This systematic review (12 studies, 2302 patients), published in Eye & ENT Research, synthesizes available evidence on the association between human metapneumovirus (HMPV) infection and otorhinolaryngological manifestations. Acute otitis media was the most frequently reported ENT manifestation, and most patients were children (88.3%). Given the marked heterogeneity across studies, the findings point to a possible association, but causality cannot be established from the current evidence.
Guided by the classic notion that a protein's amino acid sequence determines its three-dimensional structure, protein structure prediction has long been a central problem in structural biology. Over the past decade, deep learning methods, exemplified by AlphaFold2 (AF2), have revolutionized the field, an achievement recognized by the 2024 Nobel Prize in Chemistry. Yet this success does not mean the protein folding problem is fully solved. Key challenges, each an opportunity for future breakthroughs, include single-sequence prediction, modeling protein dynamics, predicting multimeric complexes, and incorporating experimental constraints.