New study examines the oral pathogen Porphyromonas gingivalis (Pg) and suggests its influence may extend beyond dental tissues. Researchers investigated whether Pg-driven periapical lesions, localized dental issues, can trigger wider metabolic disturbances through an IL-17–intense inflammatory response. Using sham-controlled mouse models without oral colonization, the researchers compared mice with and without Pg colonization to assess how IL-17 drives both tissue damage and impaired glucose regulation. The study examines whether chronic periapical infections subtly shape metabolic health and whether targeting IL-17 could offer unexpected systemic benefits.

This study systematically evaluated the potential of red rice extract as a biological ultraviolet (UV) filter and, for the first time, comprehensively validated its UV absorption characteristics, antioxidant properties, and SPF-enhancing effects in sunscreen formulations. Rich in phenolic acids, flavonoids, anthocyanins, and procyanidins, red rice extract demonstrated strong UV-absorbing capacity and free radical scavenging activity, indicating its ability to counteract UV-induced oxidative stress and inflammation.Comparative UV absorption analysis showed that the extract exhibited stable absorption peaks and favorable photothermal stability relative to three commonly used UV filters. When incorporated into oil-in-water (O/W) and water-in-oil (W/O) sunscreen formulations, red rice extract produced concentration-dependent SPF enhancement. Notably, adding 1% extract increased SPF values by more than 10% in both systems.

Importantly, the extract also showed the potential to partially replace traditional chemical UV filters. Formulations containing 1%, 3%, and 5% red rice extract were able to substitute approximately 12.82%, 19.05%, and 26.09% of chemical UV filters, respectively, without compromising SPF performance.

Overall, this work highlights red rice extract as a promising natural UV-filtering ingredient capable of boosting SPF efficacy while reducing chemical filter usage. The findings provide scientific support for its application in developing mild, safe, and environmentally friendly sunscreen products.

This study explores the profound implications of ambiguity aversion for asset price dynamics and wealth distribution. In a continuous-time macroeconomic model with heterogeneous agents and financial frictions, we demonstrate analytically and numerically that ambiguity aversion leads to a lower risk-free rate, reduced consumption, higher precautionary savings, and wealth redistribution, resulting in significant asset price misalignment. These distortions cause universal welfare loss, making a case for policy intervention. We find that while distortionary capital taxes can mitigate price misalignment, conventional monetary policy, if well-calibrated, can reduce distortions and improve welfare without such trade-offs.

A new large-scale study reveals that uncertainty in climate policy (CPU) is a significant driver for improving corporate Environmental, Social, and Governance (ESG) performance. Analysing data from 4,490 Chinese listed companies (2011-2022), researchers found a strong positive correlation between CPU and ESG scores. The primary motivation is risk mitigation: companies facing higher systemic risk use enhanced ESG performance as a strategic shield. The effect is most pronounced in non-state-owned enterprises, heavy-polluting industries, and highly competitive markets. The findings provide crucial insights for businesses strengthening sustainability strategies and for policymakers aiming to foster resilient, low-carbon economic growth.

Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials (EWAMs) thanks to their unique architecture, but their construction usually involves complex procedures and extremely depends on unidirectional freezing technique. Herein, we propose a groundbreaking approach that leverages the assemblies of salting-out protein induced by ammonium metatungstate (AM) as the precursor, and then acquire directional three-dimensional carbon-based foams through simple pyrolysis. The electrostatic interaction between AM and protein ensures well dispersion of WC_1−x nanoparticles on carbon frameworks. The content of WC_1−x nanoparticles can be rationally regulated by AM dosage, and it also affects the electromagnetic (EM) properties of final carbon-based foams. The optimized foam exhibits exceptional EM absorption performance, achieving a remarkable minimum reflection loss of − 72.0 dB and an effective absorption bandwidth of 6.3 GHz when EM wave propagates parallel to the directional pores. Such performance benefits from the synergistic effects of macroporous architecture and compositional design. Although there is a directional dependence of EM absorption, radar stealth simulation demonstrates that these foams can still promise considerable reduction in radar cross section with the change of incident angle. Moreover, COMSOL simulation further identifies their good performance in preventing EM interference among different electronic components.

Low-cost and high-safety aqueous Zn-I₂ batteries attract extensive attention for large-scale energy storage systems. However, polyiodide shuttling and sluggish iodine conversion reactions lead to inferior rate capability and severe capacity decay. Herein, a three-dimensional polyaniline is wrapped by carboxyl-carbon nanotubes (denoted as C-PANI) which is designed as a catalytic cathode to effectively boost iodine conversion with suppressed polyiodide shuttling, thereby improving Zn-I₂ batteries. Specifically, carboxyl-carbon nanotubes serve as a proton reservoir for more protonated –NH⁺ = sites in PANI chains, achieving a direct I⁰/I⁻ reaction for suppressed polyiodide generation and Zn corrosion. Attributing to this “proton-iodine” regulation, catalytic protonated C-PANI strongly fixes electrolytic iodine species and stores proton ions simultaneously through reversible –N = /–NH⁺– reaction. Therefore, the electrolytic Zn-I₂ battery with C-PANI cathode exhibits an impressive capacity of 420 mAh g⁻¹ and ultra-long lifespan over 40,000 cycles. Additionally, a 60 mAh pouch cell was assembled with excellent cycling stability after 100 cycles, providing new insights into exploring effective organocatalysts for superb Zn-halogen batteries.

Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots, facilitating energy-efficient CO₂ management in life-support systems of confined space. Here, a micro/nano-reconfigurable robot is constructed from the CO₂ molecular hunters, temperature-sensitive molecular switch, solar photothermal conversion, and magnetically-driven function engines. The molecular hunters within the molecular extension state can capture 6.19 mmol g⁻¹ of CO₂ to form carbamic acid and ammonium bicarbonate. Interestingly, the molecular switch of the robot activates a molecular curling state that facilitates CO₂ release through nano-reconfiguration, which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption. Nano-reconfiguration of robot alters the amino microenvironment, including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level. This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives, thereby inhibiting the side reactions that generate hard-to-decompose urea structures, achieving the lowest regeneration temperature of 55 °C reported to date. The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating. Notably, the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%, effectively addressing the issue of carbon suffocation in confined spaces. This work significantly enhances life-support systems for deep-space exploration, while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.

This study analyzes the cutting-edge applications of large language models (LLMs) in cardiovascular imaging: on one hand, they significantly enhance diagnostic efficiency and standardization through intelligent interpretation of multi-modal imaging data such as cardiac magnetic resonance and coronary CT; on the other hand, they demonstrate transformative potential in clinical decision support, patient communication, and scientific research data mining. The article also provides an in-depth exploration of the developmental bottlenecks and future pathways of LLMs in key areas such as cross-modal data fusion, clinical validation, and ethical standardization.