Natural biomass-derived carbon material is one promising alternative to traditional graphene-based catalyst for oxygen electrocatalysis. However, their electrocatalytic performance were constrained by the limited modulating strategy. Herein, using N-doped commercial coconut shell-derived activated carbon (AC) as catalyst model, the controllably enhanced sp²-C domains, through an flash Joule heating process, effectively improve the edge defect density and overall graphitization degree of AC catalyst, which tunes the electronic structure of N configurations and accelerates electron transfer, leading to excellent oxygen reduction reaction performance (half-wave potential of 0.884 V_RHE, equivalent to commercial 20% Pt/C, with a higher kinetic current density of 5.88 mA cm^-2) and oxygen evolution reaction activity (overpotential of 295 mV at 10 mA cm²). In a Zn-air battery, the catalyst shows outstanding cycle stability (over 1200 h) and a peak power density of 121 mW cm^-2, surpassing commercial Pt/C and RuO₂ catalysts. Density functional theory simulation reveals that the enhanced catalytic activity arises from the axial regulation of local sp²-C domains. This work establishes a robust strategy for sp²-C domain modulation, offering broad applicability in natural biomass-based carbon catalysts for electrocatalysis.

Rational design of multifunctional nanoplatforms capable of combining therapeutic effects with real-time monitoring of drug distribution and tumor status is emerging as a promising approach in cancer nanomedicine. Here, we introduce pyropheophorbide a–bisaminoquinoline conjugate lipid nanoparticles (PPBC LNPs) as a bimodal system for image-guided phototherapy in bladder cancer treatment. PPBC LNPs not only demonstrate both powerful photodynamic and photothermal effects upon light activation, but also exhibit potent autophagy blockage, effectively inducing bladder cancer cell death. Furthermore, PPBC LNPs possess remarkable photoacoustic (PA) and fluorescence (FL) imaging capabilities, enabling imaging with high-resolution, deep tissue penetration and high sensitivity for tracking drug biodistribution and phototherapy efficacy. Specifically, PA imaging confirms the efficient accumulation of PPBC LNPs within tumor and predicts therapeutic outcomes of photodynamic therapy, while FL imaging confirms their prolonged retention at the tumor site for up to 6 days. PPBC LNPs significantly suppress bladder tumor growth, with several tumors completely ablated following just two doses of the nanoparticles and laser treatment. Additionally, PPBC LNPs were formulated with lipid-based excipients and assembled using microfluidic technology to enhance biocompatibility, stability, and scalability, showing potential for clinical translation. This versatile nanoparticle represents a promising candidate for further development in bladder cancer therapy.

Abstract

Purpose – This article aims to examine whether corporate green investment intentions were inhibited by the online concerns of retail investors, a group accounting for more than 90% of the total stock investors in China.

Design/methodology/approach – A panel regression model is used to examine whether retail investor concerns inhibit corporate green investment intentions based on data from Chinese listed companies and data extracted from online social platforms where retail investors exchange information from 2010 to 2022. Machine learning methods are used to construct text word frequency indicators representing corporate green investment intentions. A series of endogeneity and robustness tests and a heterogeneity analysis are used to examine the regression results.

Findings – This article finds that retail investor concerns shown on online social platforms significantly inhibit corporate green investment intentions. The inhibition effect comes from the investment stages of source prevention and process control, while a promotion effect is identified at the stage of end-pipe treatment. Furthermore, the inhibition effect is smaller for companies with improved credibility of information disclosure.

Originality/value – This article innovatively uses the word frequency construction method based on text data to measure green investment intentions after clarifying the concept of green investment, which differs from green transformation, social responsibility, green finance and other popular terms. This article focuses on the emerging online social platform instead of discussing the function and mechanism of traditional information intermediaries. By verifying the market pressure caused by retail investor concerns about corporate green investment, this article expands the coverage of the market pressure hypothesis from traditional media to online social platforms and provides an empirical basis for implementing the national policy of de-retailer. This article’s validation of endogeneity is comprehensive compared to the literature on the selection of instrumental variables based on regional or sectoral averages.

A study in Science China Life Sciences reveals how hybrid fish maintain fertility despite genomic divergence. By analyzing structural variations, gene expression, and chromatin accessibility in testicular cells, researchers identified conserved allelic and testis-specific genes, with rnf212b as a key regulator of reproductive traits.

Researchers discovered the spin-configuration of excited states in a promising zero-dimensional luminescent material, (Bmpip)₂SnBr₄, resolved a scientific debate with groundbreaking insights into its unique energy structures and shed light on designing better LEDs and spin-based devices.

Recently, Hangzhou Institute of Medicine (HIM), University of Chinese Academy of Sciences (UCAS), Guangzhou National Laboratory and other research institutes published a perspective entitled Redefining imaging genomics for the next decade on Science Bulletin, in which the article systematically summarizes the existing advancements in imaging genomics, and proposes a framework for imaging genomics that provide a new path for precision medicine.

This study reviews how optimization techniques can improve the economic dispatch of local energy sources, helping reduce costs, enhance grid reliability, and support renewable integration. By comparing classical and heuristic methods, it identifies strategies that align with the UN Sustainable Development Goals (SDGs), particularly affordable and clean energy (SDG 7) and climate action (SDG 13), contributing to a more sustainable and efficient decentralized power system.

In recent years, the large-scale grid connection of various distributed power sources has made the planning and operation of distribution grids increasingly complex. Consequently, a large number of active distribution network reconfiguration techniques have emerged to reduce system losses, improve system safety, and enhance power quality via switching switches to change the system topology while ensuring the radial structure of the network. While scholars have previously reviewed these methods, they all have obvious shortcomings, such as a lack of systematic integration of methods, vague classification, lack of constructive suggestions for future study, etc. Therefore, this paper attempts to provide a comprehensive and profound review of 52 methods and applications of active distribution network reconfiguration through systematic method classification and enumeration. Specifically, these methods are classified into five categories, i.e., traditional methods, mathematical methods, meta-heuristic algorithms, machine learning methods, and hybrid methods. A thorough comparison of the various methods is also scored in terms of their practicality, complexity, number of switching actions, performance improvement, advantages, and disadvantages. Finally, four summaries and four future research prospects are presented. In summary, this paper aims to provide an up-to-date and well-rounded manual for subsequent researchers and scholars engaged in related fields.

A new study shows that treating mesenchymal stem cells with lipopolysaccharide (LPS) shifts their energy use toward glycolysis, reducing their healing potential in stroke therapy — offering insights into improving cell-based treatments for brain injuries.