The research team at the Department of Chemistry at KAIST has achieved a breakthrough by selectively converting waste tires into high-purity cyclic alkenes, valuable chemical building blocks used in the production of rubber and nylon fibers.

As environmental pollutants pose a serious threat to socioeconomic and environmental health, the development of simple, efficient, accurate and cost-effective methods for pollution monitoring and control remains a major challenge, but it is an unavoidable issue. In the past decade, the artificial nanozymes have been widely used for environmental pollutant monitoring and control, because of their low cost, high stability, easy mass production, etc. However, the conventional nanozyme technology faces significant challenges in terms of difficulty in regulating the exposed crystal surface, complex composition, low catalytic activity, etc. In contrast, the emerging single-atom nanozymes (SANs) have attracted much attention in the field of environmental monitoring and control, due to their multiple advantages of atomically dispersed active sites, high atom utilization efficiency, tunable coordination environment, etc. To date, the insufficient efforts have been made to comprehensively characterize the applications of SANs in the monitoring and control of environmental pollutants. Building on the recent advances in the field, this review systematically summarizes the main synthesis methods of SANs and highlights their advances in the monitoring and control of environmental pollutants. Finally, we critically evaluate the limitations and challenges of SANs, and provide the insights into their future prospects for the monitoring and control of environmental pollutants.

Manganese-based chalcogenides have significant potential as anodes for sodium-ion batteries (SIBs) due to their high theoretical specific capacity, abundant natural reserves, and environmental friendliness. However, their application is hindered by poor cycling stability, resulting from severe volume changes during cycling and slow reaction kinetics due to their complex crystal structure. Here, an efficient and straightforward strategy was employed to in-situ encapsulate single-phase porous nanocubic MnS_0.5Se_0.5 into carbon nanofibers using electrospinning and the hard template method, thus forming a necklace-like porous MnS_0.5Se_0.5-carbon nanofiber composite (MnS_0.5Se_0.5@N-CNF). The introduction of Se significantly impacts both the composition and microstructure of MnS_0.5Se_0.5, including lattice distortion that generates additional defects, optimization of chemical bonds, and a nano-spatially confined design. In situ/ex-situ characterization and density functional theory calculations verified that this MnS_0.5Se_0.5@N-CNF alleviates the volume expansion and facilitates the transfer of Na⁺/electron. As expected, MnS_0.5Se_0.5@N-CNF anode demonstrates excellent sodium storage performance, characterized by high initial Coulombic efficiency (90.8%), high-rate capability (370.5 mAh g^-1 at 10 A g^-1) and long durability (over 5000 cycles at 5 A g^-1). The MnS_0.5Se_0.5@N-CNF//NVP@C full cell, assembled with MnS_0.5Se_0.5@N-CNF as anode and Na₃V₂(PO₄)₃@C as cathode, exhibits a high energy density of 254 Wh kg^-1 can be provided. This work presents a novel strategy to optimize the design of anode materials through structural engineering and Se substitution, while also elucidating the underlying reaction mechanisms.

research team recreates sea silk from discarded pen shells byssus—drawing attention as an eco-friendly and sustainable textile.

The researchers developed a green and simple method to synthesize a silica aerogel that integrates two contrasting functional groups including methyl and amine. The aerogel not only has high adsorption capacity for low-concentration CO₂ but also possesses excellent thermal insulation performance under humid and high-temperature conditions.

Objectives: This systematic review aimed to assess the properties and feasibility of existing risk pre diction models for post-intensive care syndrome outcomes in adult survivors of critical illness. Methods: As of November 1, 2023, Cochrane Library, PubMed, Embase, CINAHL, Web of Science, PsycInfo, China National Knowledge Infrastructure (CNKI), SinoMed, Wanfang database, and China Science and Technology Journal Database (VIP) were searched. Following the literature screening process, we extracted data encompassing participant sources, post-intensive care syndrome (PICS) outcomes, sample sizes, missing data, predictive factors, model development methodologies, and metrics for model per formance and evaluation. We conducted a review and classification of the PICS domains and predictive factors identified in each study. The Prediction Model Risk of Bias Assessment Tool was employed to assess the quality and applicability of the studies. Results: This systematic review included a total of 16 studies, comprising two cognitive impairment studies, four psychological impairment studies, eight physiological impairment studies, and two studies on all three domains. The discriminative ability of prediction models measured by area under the receiver operating characteristic curve was 0.68e0.90. The predictive performance of most models was excellent, but most models were biased and overfitted. All predictive factors tend to encompass age, pre ICU functional impairment, in-ICU experiences, and early-onset new symptoms. Conclusions: This review identified 16 prediction models and the predictive factors for PICS. Nonetheless, due to the numerous methodological and reporting shortcomings identified in the studies under review, clinicians should exercise caution when interpreting the predictions made by these models. To avert the development of PICS, it is imperative for clinicians to closely monitor prognostic factors, including the in ICU experience and early-onset new symptoms.

The rapid advancement of single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) has opened unprecedented windows into cellular diversity, yet existing methods for multiplexing samples struggle with scalability and accuracy. Traditional techniques relying on antibodies or lipid-based barcodes often fail to uniformly label cells across different types or species, particularly in complex clinical samples. These limitations—cell-type bias, cross-contamination risks, and loss of rare cell populations—hinder large-scale studies and clinical translation. To overcome these challenges, a team led by Professor Yiwei Li at Huazhong University of Science and Technology (HUST) has pioneered Toti-N-Seq, a groundbreaking technology that harnesses the universal presence of N-glycans on cell and nuclear surfaces. Published as a cover story in Research (2025, DOI: 10.34133/research.0678), this innovation redefines how researchers approach high-throughput cellular profiling.