A comprehensive review published in Science China Life Sciences by a collaborative team led by Prof. Wenjie Shu (Bioinformatics Center of AMMS) et al. highlights that Protein Foundation Models (pFMs) have emerged as game-changers in life science.

These AI tools, trained on large-scale datasets, can predict protein characteristics and design new proteins with desired functions. This review explores the progress, uses, challenges, and future of pFMs. It looks at the diverse data—from genetic sequences to 3D structures and functional information—that these models learn from. It covers key AI methods and highlights real-world impacts in research, protein design, and medicine. The article also discusses major challenges, including data scarcity and the complexity of validating model outputs. Looking ahead, the review highlights promising developments, such as modeling protein interactions and building virtual cell systems, which have the potential to enpower the next generation of bioengineering. This comprehensive overview serves as both a valuable resource for computational researchers and a strategic reference for scientists using these tools in related fields.

Researchers at the University of Oulu, Finland, have developed a pine‑bark–based water‑treatment medium that efficiently removes antibiotics as well as residues of blood‑pressure and antidepressant medicines from wastewater treatment plant effluent. A new doctoral thesis reports promising results with a simple and low‑cost method in which pine bark was modified with iron.

Space exploration is significant for scientific innovation, resource utilization, and planetary security. Space exploration involves several systems including satellites, space suits, communication systems, and robotics, which have to function under harsh space conditions such as extreme temperatures (− 270 to 1650 °C), microgravity (10^-6 g), unhealthy humidity (< 20% RH or > 60% RH), high atmospheric pressure (~ 1450 psi), and radiation (4000–5000 mSv). Conventional energy-harvesting technologies (solar cells, fuel cells, and nuclear energy), that are normally used to power these space systems have certain limitations (e.g., sunlight dependence, weight, degradation, big size, high cost, low capacity, radioactivity, complexity, and low efficiency). The constraints in conventional energy resources have made it imperative to look for non-conventional yet efficient alternatives. A great potential for enhancing efficiency, sustainability, and mission duration in space exploration can be offered by integrating triboelectric nanogenerators (TENGs) with existing energy sources. Recently, the potential of TENG including energy harvesting (from vibrations/movements in satellites and spacecraft), self-powered sensing, and microgravity, for multiple applications in different space missions has been discussed. This review comprehensively covers the use of TENGs for various space applications, such as planetary exploration missions (Mars environment monitoring), manned space equipment, In-orbit robotic operations /collision monitoring, spacecraft's design and structural health monitoring, Aeronautical systems, and conventional energy harvesting (solar and nuclear). This review also discusses the use of self-powered TENG sensors for deep space object perception. At the same time, this review compares TENGs with conventional energy harvesting technologies for space systems. Lastly, this review talks about energy harvesting in satellites, TENG-based satellite communication systems, and future practical implementation challenges (with possible solutions).

Women who receive continuous care from community-based midwives have a significantly reduced risk of preterm birth in comparison to those who receive standard care. This care model also significantly reduced risks of preterm births in women who are at greatest social risk of adverse outcomes.