Epigenetic modifiers, enzymes that catalyze covalent modifications on chromatin, play a pivotal role in establishing stable states for gene expression and cellular identity. Mutations in these modifiers have been linked to a variety of human diseases, including developmental disorders and cancers, highlighting the importance of understanding how these mutations impact the functions of epigenetic modifiers in development and disease. Recent findings suggest that some epigenetic modifiers may have noncatalytic functions, independent of their catalytic activities, which raises questions about the determinants of their dependency on catalytic activity and the implications for chromatin modifications. In this context, a comment by Chen et al. provides valuable insights into the catalytic and noncatalytic functions of the histone methyltransferase SETD2, a protein responsible for histone H3 lysine 36 trimethylation (H3K36me3) and frequently mutated in clear cell renal cell carcinoma.

This review focuses on the applications of cutting-edge ultrafast nano-spectroscopy and nano-imaging based on diverse tip-based microscopy techniques. These advanced techniques simultaneously achieve sub-diffraction spatial resolution facilitated by a subwavelength tip apex and high temporal resolution enabled by electromagnetic pulses. This spatiotemporally resolved capability enables real-time visualization of light-matter interactions, uncovering phenomena like polaritons, quantum phases, and many-body effects across various materials, including 2D, molecular, and hybrid systems.

In a review buplished in MedComm, the author highlights the critical role of metabolomics in identifying therapeutic targets for drug discovery. Metabolomics can capture phenotypic changes induced by exogenous compounds, offering a valuable approach beyond traditional protein-level focus. The review outlines various metabolomics-based methods, such as dose-response metabolomics and stable isotope-resolved metabolomics, which can identify key enzymes and metabolic pathways affected by drugs. The author emphasizes importance of metabolomics in advancing disease mechanism understanding and accelerating targeted drug development, while acknowledging current challenges in the field.

A research team led by Prof. HU Li at the Institute of Psychology of the Chinese Academy of Sciences, has revealed that parvalbumin (PV) interneurons in the primary somatosensory cortex (S1) preferentially encode pain intensity and drive nociceptive-evoked gamma oscillations (GBOs).

Wireless surface acoustic wave (SAW) sensors hold great promise for in-situ, real-time monitoring and accurately assessing the health status of hot-end components. However, the thin-film electrode as the SAW sensor core unit with excellent high-temperature conductivity, stability, and oxidation resistance is still a challenge, especially in ultra-high temperature harsh environments. Polymer-derived ceramics (PDCs) method has attracted great attention because of the advantages of rapid preparation of film and adjustable thickness of film. PDC SiHfBCN ceramics have been proved promising ceramics for ultra-high-temperature applications due to excellent high-temperature stability and oxidation resistance up to 1500 °C. However, the high-temperature electrical conductivity of PDC SiHfBCN ceramic coating, especially above 1000 °C, have not been reported yet. The relationship between microstructure and electrical conductivity at high temperatures was established to explain the conductive mechanism for the first time.

Hydrogen peroxide is an environmentally friendly and powerful oxidant that is used in a variety of industries. At industry-scale, it is currently manufactured using a process called anthraquinone oxidation-reduction process, but researchers are searching for a better way. An electrocatalytic oxygen reduction reaction (ORR) is a safe, clean, and reliable method, but an effective catalyst has yet to be identified and adopted widely because of low selectivity.

Computer vision is used in many sectors for its ability to monitor and analyze visual data in ways that extend past what human vision can do. This includes the medical, agricultural, and industrial sectors where, for example, early tumor detection, early pest detection and fine quality control can save both money and, most importantly, lives. For computer vision one of the most challenging functions is camouflage object detection (COD), the ability to recognize, identify and analyse an object in an image or video that is difficult to differentiate from its background. Since 2023 there has been a surge in research on COD in conjunction with the use of deep learning, a type of machine learning. This has created a large pool of research that has not yet been surveyed. To address this a research group at Duke University and Tsinghua University has undertaken an extensive review of the COD literature to catalogue, review and analyze the current state of the field.