SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3584-3
Sutures, as necessary medical devices for postoperative treatment, are no longer merely supportive but are required to have advanced functions to promote repair. Here, we report an absorbable self-powered electrical stimulation suture (SES-suture). The suture is composed entirely of absorbable materials (magnesium, polylactic acid, and polycaprolactone) and can be used in vivo for incision closure and repair. The suture has the capacity to generate spontaneous electrical stimulation in response to body movement, allowing for accelerated tissue reconstruction. An in vivo muscle incision repair model in rabbits demonstrated that the wound healing rate under treatment with this suture was 1.6 times faster than that of commercial sutures, proving its postoperative therapeutic capability. Immunofluorescence and quantitative analyses showed that SES-sutures significantly increased α-SMA and CD31 expression, with levels approximately 2.8 and 3.2 times higher than the blank group, respectively, indicating enhanced angiogenesis and muscle regeneration. The SES-suture exhibited excellent mechanical properties, sustained electrical output, structural and functional stability after implantation, and good biocompatibility. This large animal approach offers crucial translational evidence for potential human applications, addressing the limitations of rodent models due to differences in biomechanics and regeneration rates. While the biosafety profile requires further long-term evaluation, the findings strongly suggest that SES-sutures represent a promising therapeutic strategy for enhancing tissue regeneration and functional recovery.
Journal of Fuel Chemistry and Technology•2026•DOI: 10.1016/S1872-5813(25)60607-4
The methanation of biomass gasification syngas (H2/CO = 3:1) was investigated over Ni/Al2O3 monolithic catalysts supported on cordierite, with a nominal Ni loading of 15 wt%. Catalysts were modified by treatment with 10% NaOH solution for 1 h and 2 h. Physicochemical properties were characterized by BET, TEM, H2-TPR, XRD, CO2-TPD, and TG. Results showed that the 2 h modification (15%Ni/Al2O3-2h) increased specific surface area, enhanced catalytic activity, and increased alkaline site density compared to the unmodified catalyst. Under optimized conditions (H2/CO volume ratio 3:1, space velocity 10000 mL/(g·h), temperature 400 °C), the 15%Ni/Al2O3-2h catalyst achieved a CO conversion of 97% and CH4 selectivity of 100%. Stability tests over 2 h showed that the CO conversion remained stable at approximately 98%, indicating excellent catalytic stability. The study demonstrates that alkali modification with 10% NaOH for 2 h significantly improves both the methanation performance and stability of Ni/Al2O3 monolithic catalysts, offering a promising route for synthetic natural gas production from biomass.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202604025
To meet the minute-level early-warning requirements for odor and multi-pollutant emissions at waste treatment facilities, this study proposed a multivariate short-term time-series prediction framework applicable to multi-tier scenarios covering source and boundary points (i.e., workshops and plant boundaries). Based on continuous online monitoring data with a 5-second resolution, a long short-term memory (LSTM) model using a sliding-window and recursive multi-step prediction strategy was constructed to jointly model odor concentration (OU) and pollutants including VOCs, NH3, H2S, and CH3SH (mg/m³). An evaluation protocol aligned with environmental supervision practice was established, incorporating mean absolute error (MAE), root mean square error (RMSE), goodness-of-fit (R²), skill scores (SS) relative to a persistence baseline, and threshold-based error stratification to characterize uncertainty during peak emission periods. The results showed that at workshop monitoring sites with relatively stable operating conditions, VOCs, NH3, H2S, and CH3SH exhibited a high goodness of fit and low prediction errors. In contrast, at boundary sites affected by plume arrival delays and diffusion-dilution non-stationarity, OU and VOCs displayed significantly amplified errors during peak episodes, and the skill score advantage over the baseline became unstable at certain sites. Stratified analysis consistently revealed that non-peak periods outperformed peak periods, indicating that event-driven fluctuations were the main sources of error. Accordingly, this study suggested incorporating exogenous variables such as wind speed and direction, ventilation and gate access control, and operational rhythms, along with peak-sensitive loss functions, into the model to enhance its capacity to characterize and provide early warnings for transient emission pulses. Overall, this study established a reusable methodological baseline and evaluation paradigm for minute-scale multi-pollutant prediction, providing quantitative support for the operational management and source-to-boundary coordinated control of waste treatment facilities.