Enhancing the firefighting protective clothing with exceptional thermal barrier and temperature sensing functions to ensure high fire safety for firefighters has long been anticipated, but it remains a major challenge. Herein, inspired by the human muscle, an anisotropic fire safety aerogel (ACMCA) with precise self-actuated temperature monitoring performance is developed by combining aramid nanofibers with eicosane/MXene to form an anisotropically oriented conductive network. By combining the two synergies of the negative temperature-dependent thermal conductive eicosane, which induces a high-temperature differential, and directionally ordered MXene that establishes a conductive network along the directional freezing direction. The resultant ACMCA exhibited remarkable thermoelectric properties, with S values reaching 46.78 μV K^-1 and κ values as low as 0.048 W m^-1 K^-1 at room temperature. Moreover, the prepared anisotropic aerogel ACMCA exhibited electrical responsiveness to temperature variations, facilitating its application in intelligent temperature monitoring systems. The designed anisotropic aerogel ACMCA could be incorporated into the firefighting clothing as a thermal barrier layer, demonstrating a wide temperature sensing range (50–400 °C) and a rapid response time for early high-temperature alerts (~ 1.43 s). This work provides novel insights into the design and application of temperature-sensitive anisotropic aramid nanofibers aerogel in firefighting clothing.

In a paper published in SCIENCE CHINA Earth Sciences, a team of researchers analyzed spatiotemporal distribution, organizational modes of severe convective wind (SCW) events during the warm season (May to September) in North China. In addition, the environmental conditions before the occurrence of SCW convective systems and non-SCW convective systems were compared. It provides valuable insights to enhance the forecasting accuracy of severe convective weather events in this region.

Biological cells exhibit nearly transparent characteristics with weak absorption properties in the visible light spectrum, resulting in extremely low optical contrast between cells and the surrounding medium under traditional bright-field microscopy. To enhance imaging contrast, conventional methods rely on chemical staining or fluorescent labeling, introducing exogenous absorption/fluorescence probes to visualize cellular structures. However, these approaches suffer from drawbacks such as phototoxicity, photobleaching, and poor biocompatibility, severely limiting long-term dynamic observation of living cells. Quantitative phase imaging (QPI) utilizes the inherent physical property of cellular phase (thickness) as an endogenous “probe”, resolving cellular thickness, refractive index, and 3D topography with nanoscale accuracy. It provides a new avenue for dynamic observation of living cells and nanoscale biological studies.

As a significant branch of QPI technology, differential phase contrast (DPC) has attracted considerable attention due to its advantages of being non-interferometric and low-cost. However, its theoretical framework relies on the “weak object approximation”, linking intensity images to sample phase through a linear model. This simplified model introduces two fundamental limitations. First, the phase reconstruction result is highly dependent on the precise modeling of the phase transfer function (PTF) under an ideal pupil. In practical optical systems, however, wavefront aberrations couple with the sample phase, leading to significant reconstruction errors. Second, the conventional half-circle illumination suffers from the problem of PTF response cancellation, resulting in the loss of low-frequency phase information and making it difficult to accurately reconstruct the fine structure of weak phase objects. These limitations significantly compromise the robustness of DPC in non-ideal optical environments and restrict its practical applicability in frontier biological research, such as cellular morphology characterization and tracking of subcellular dynamic processes.

NANJING, China – In a revolutionary one-two punch, Chinese research teams have successfully engineered the human spleen into a living bioreactor capable of curing diabetes and growing functional organs – achievements published back-to-back in Science Translational Medicine and Diabetes this month. This convergence of discoveries positions the long-underestimated spleen as a game-changing platform for regenerative medicine.

In a position paper published in Journal of Geo-information Science, a team of scientists mainly from Chinese Academy of Sciences advocate the potential of recursive intelligent geographic modeling based on the "data-knowledge-model" tripartite collaboration. They highlight the fundamental role of domain modeling knowledge driving geocomputation with geospatial data to achieve successful geographic model workflow adaptive to application context.

Grapevines, widely valued for their fruit and wine, are especially vulnerable to cold temperatures.