Increasing atmospheric carbon dioxide (CO₂) levels pose a significant global challenge, making the assessment of natural carbon sinks, such as forests, ever more critical. New research conducted in the Garhwal region of the Indian Himalayas investigates how different forest types contribute to carbon storage across varying altitudes. The investigation by Arvind Singh, Vinod Prasad Khanduri, and colleagues identifies distinct carbon partitioning strategies, where high-altitude conifer forests excel at storing carbon in biomass, while lower-elevation mixed broadleaf forests are superior in stabilizing soil carbon. This understanding is vital for developing effective climate mitigation plans.

For more than two decades, the Global Positioning System (GPS) constellation has silently monitored high-energy electrons in Earth's radiation belts—but inconsistencies among its satellites have prevented scientists from fully trusting the combined data. 

A research team has proposed a new framework for understanding how traditional Chinese medicine (TCM) works at the tissue level by using artificial intelligence (AI), single-cell omics, and spatial omics to decode “cell niches”—local microenvironments where multiple cell types interact. 

Precise regulation of reactive oxygen species (ROS) is central to the advancement of next-generation therapies for infected wound healing, where dynamic redox balance is essential for effective treatment and tissue repair. In this context, a pH-responsive bifunctional nanozyme, constructed by coupling sub-nanoscale 12-phosphotungstic acid clusters with Fe₃O₄ nanoparticles, has emerged as a promising inorganic catalytic platform. By responding to the acidic microenvironment of infected wounds, the nanozyme enhances antibacterial activity through ROS generation, while subsequently scavenging excess ROS during the healing phase, thereby promoting tissue regeneration and alleviating inflammation

An research article published in Nano Research provides a comprehensive review of the latest advancements in ADCs, particularly distinguishing different structural subclasses and linking structural types with asymmetric catalytic mechanisms. It discusses the role of artificial intelligence (AI) in the high-throughput screening, performance prediction, and elucidation of catalytic mechanisms of ADCs. The review also highlights the intrinsic logical advancements in characterization techniques and the applications of ADCs in key electrocatalytic reactions, such as the oxygen reduction reaction (ORR), oxygen evolution reaction (OER), hydrogen evolution reaction (HER), and carbon dioxide reduction reaction (CO2RR).

Lithium-sulfur (Li-S) batteries offer exceptional theoretical energy density and specific capacity, but their practical development has been limited by sluggish sulfur reduction reaction (SRR) kinetics and severe “shuttle effect” caused by soluble lithium polysulfides (LiPSs). To address these challenges, this work proposes an electron-injection-softened strategy to achieve a nearly barrier-free cascaded SRR. By constructing a Co₉S₈-Mn₃O₄@CNF heterostructure, electrons are injected from Co₉S₈ to Mn₃O₄, softening its surface and inducing “soft to soft” orbital interactions with LiPSs. This design allows for rapid electron transfer and efficient Li₂S₂/Li₂S formation, resulting in a 2-Ah-level stable Li-S pouch cell.

Since their discovery in 2011, MXenes have been extensively applied across many fields due to their high specific surface area, high electrical conductivity, lightweight and adjustable bandgap. MXenes are distinct from other 2D layered materials because their unique synthesis inevitably introduces surface-terminated groups, which have a significant impact on their physical and chemical properties. This review introduces the various types of MXene materials and delves into the mechanisms for the generation of terminal groups during the preparation process. Then, it comprehensively analyzes how these functionalized terminal groups significantly affect the performance of MXene materials in different application scenarios and summarizes their potential and advantages in practical applications.

A major challenge in cuproptosis-based cancer therapy is achieving tumor-selective activation without relying on external copper administration. Published in Biomedical Analysis, a new study from Guizhou Medical University introduces an iRGD-modified PLGA-PEG nanoparticle system that delivers the copper-chelating agent TPEN directly to tumor cells. By exploiting the high copper levels already present in cancer cells, this approach triggers copper-dependent cell death while reducing potential systemic toxicity associated with metal delivery.