For decades, Alzheimer’s disease (AD) research has focused on its visible villains—amyloid plaques and tau tangles. But beneath the surface, another player may be quietly steering the disease’s course: lipid metabolism. Lipids, the essential substances that build and fuel the brain, are proving to be powerful influencers of disease progression. When their balance falters, harmful proteins accumulate, synapses weaken, and inflammation spreads. This new review pulls together cutting-edge findings that link genetic risk factors, like APOE4, to disrupted cholesterol transport, faulty fat storage, and poor lipid clearance—unveiling a hidden layer of AD biology and pointing toward untapped therapeutic strategies.

Passive daytime radiative cooling materials are promising for energy-free cooling as global energy consumption rises. SrZrO₃ crystals, with their wide band gap and infrared photon lattice vibration absorption, are potential candidates for such applications. Most importantly, Zn doping has been shown to enhance both solar reflectivity and atmospheric window emissivity, which are critical for cooling performance. Despite the recognized potential of SrZrO₃-based materials, the systematic understanding of how specific dopants like Zn synergistically modify the spectral radiative characteristics, and ultimately the passive cooling performance through combined effects on electronic structure, grain morphology, and lattice symmetry has yet to be comprehensively established. Filling this research gap is imperative for the rational design of high-performance radiative cooling materials.

Recently, Associate Professor Wushuang Zhang et al. from Southwest University, China Agricultural University, and the Chinese Academy of Agricultural Sciences systematically reviewed the practices and achievements of green technology innovations in major food crops from 2000 to 2022. They aimed to answer the question: how can China’s agriculture achieve a balance between “high yield” and “high efficiency” amid increasing resource constraints? The related paper has been published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2025633).

Recently, Professor Lin Ma et al. from Nanjing University, China Agricultural University, and Hebei Agricultural University proposed a new agricultural system research method that combines “top-down” and “bottom-up” approaches, providing a viable pathway to address this dilemma. The related paper has been published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2025628).

Recently, Professor Wenfeng Cong et al. from China Agricultural University proposed a solution called “green technology”, validated through over 12,000 field comparison trials conducted via a nationwide collaborative network. This research not only addresses the aforementioned challenges but also introduces a novel agricultural research paradigm—the “12345” model. This model emphasizes starting from actual production needs and resolving the dual contradictions between high yield and environmental protection, as well as economic growth and ecological preservation, through multidisciplinary collaboration and participation from multiple stakeholders. The relevant paper has been published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2025630).

A high throughput synthesis method is established to produce ultrathin MOF nanosheets and nanosheet membranes within only 30 min, shedding light on 2D high-performance membrane customization for separation and purification requirements.

In a paper published in Frontiers of Engineering Management, researchers reveal significant regional disparities in China's WEEE generation: central/eastern regions exhibit higher stockpiles but slower growth, while western areas show lower baselines yet faster expansion—with computers and air conditioners displaying the most rapid obsolescence rates and institutional sources presenting high uncertainty. The findings underscore the urgent need for coordinated regional recycling strategies and prioritized category governance.

In a study published in Frontiers of Engineering Management, researchers from Huazhong University of Science and Technology present an online hidden Markov model (OHMM) for predicting geological risks during tunnel excavation.  Applied to a tunnel excavation project in Singapore, the OHMM outperformed conventional methods, accurately forecasting geological risks ahead of the tunnel boring machine using minimal historical data.