The review was led by Prof. Shaorong Gao of Tongji University, in collaboration with researchers from multiple universities and research institutes across China. It examines how epigenetic mechanisms decide which genes are used, when they are used and how strongly they are expressed - from the earliest stages of development to aging, cancer and therapy.

Bringing together evidence from reproduction, embryonic development, stem-cell research, tissue maintenance, aging, cancer and clinical translation, the review assesses what these mechanisms may mean for reproductive medicine, regenerative medicine and precision treatment. It also distinguishes promising directions from interventions that still require stronger evidence on delivery, specificity and long-term safety.

In a paper published in SCIENCE CHINA Earth Sciences, researchers at Sun Yat-sen University developed an SFA-based Climate Prediction (SCP) method, which directly extracted slow-varying predictable signals from observed precipitation data and applied it to seasonal prediction of summer precipitation over South China. Independent forecasts for 2011–2022 show that the SCP method achieves a regional mean temporal correlation coefficient of 0.36 and accurately predicted the sign of regional-mean precipitation anomalies in 10 of 12 summers, outperforming two dynamical models and a hybrid dynamical–statistical prediction system. The study provides a new perspective to identifying potentially predictable signals and improving regional seasonal precipitation prediction.

Robots often learn from historical experience collected under older controllers and physical conditions. When tasks, hardware or environments change, that data can become misleading. Researchers developed Occupancy-Matching Policy Optimization (OMPO), which anchors large replay buffers to a small set of recent interactions. Across locomotion, transfer, manipulation and a real-robot test, OMPO improved stability, sample efficiency and adaptation.

A new study published in Biomedical Analysis reports a protein-coated nanoparticle platform that combines the powerful light-to-heat conversion ability of copper sulfide with the biological compatibility of albumin, offering a potential strategy for safer photothermal cancer therapy.

A new study in Energetic Materials Frontiers provides a detailed picture of how aluminum combustion evolves after detonation and how this process contributes to the sustained thermal and blast-wave effects of CL-20-based thermobaric explosives. By combining high-speed infrared thermography, blast-wave measurements and theoretical modeling, the researchers show that thermobaric explosives differ fundamentally from TNT in the spatial organization and temporal evolution of their fireballs. More importantly, the work identifies a key transition around 30 ms after detonation, when the dominant contribution shifts from early oxygen-deficient aluminum combustion to secondary post-combustion involving entrained atmospheric oxygen.