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Abstract This paper aims to address the issue of environmental pollution resulting from marine oil spills by evaluating the oil adsorption performance of commonly used fence materials. Conventional oil adsorption materials exhibit limited rates and capacities for oil adsorption. Existing methods have proven insufficient in meeting the requirements for efficient and rapid oil–water separation. A new oil-absorbing barrier was developed by utilizing high oil adsorption resin as the primary material and hydroxypropyl methyl cellulose (HPMC) as the binder, leveraging the exceptional oil adsorption and hydrophobic properties of P(BMA-SMA-St)/MIL-101(Fe) resin. The oil-absorbing fence was characterized using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA). The oil adsorption rates of carbon tetrachloride, toluene, diesel and gasoline by the oil adsorption fence with 25 g/L resin content were 101.26 g/m2, 68.12 g/m2, 35.19 g/m2, and 46.69 g/m2, respectively. After 120 h of UV irradiation, the coating’s oil absorption capacity remained nearly unchanged, and it demonstrated outstanding mechanical, chemical, and wear resistance. As a result, the oil adsorption fence possesses the capability to rapidly absorb oil from the water’s surface during the process of containing oil pollution, leading to positive social and economic impacts.

Abstract Objective This study aimed to explore the characteristics of carbapenem-resistant Enterobacterales (CRE) patients in the intensive care unit (ICU) in different regions of Henan Province to provide evidence for the targeted prevention and treatment of CRE. Methods This was a cross-sectional study. CRE screening was conducted in the ICUs of 78 hospitals in Henan Province, China, on March 10, 2021. The patients were divided into provincial capital hospitals and nonprovincial capital hospitals for comparative analysis. Results This study involved 1009 patients in total, of whom 241 were CRE-positive patients, 92 were in the provincial capital hospital and 149 were in the nonprovincial capital hospital. Provincial capital hospitals had a higher rate of CRE positivity, and there was a significant difference in the rate of CRE positivity between the two groups. The body temperature; immunosuppressed state; transfer from the ICU to other hospitals; and use of enemas, arterial catheters, carbapenems, or tigecycline at the provincial capital hospital were greater than those at the nonprovincial capital hospital (P

Objective. To assess the effect of adding coagulation indices to the currently existing prognostic prediction models of traumatic brain injury (TBI) in the prediction of outcome. Methods. A total of 210 TBI patients from 2017 to 2019 and 131 TBI patients in 2020 were selected for development and internal verification of the new model. The primary outcomes include death at 14 days and Glasgow Outcome Score (GOS) at 6 months. The performance of each model is evaluated by means of discrimination (area under the curve (AUC)), calibration (Hosmer-Lemeshow (H-L) goodness-of-fit test), and precision (Brier score). Results. The IMPACT Core model showed better prediction ability than the CRASH Basic model. Adding one coagulation index at a time to the IMPACT Core model, the new combined models IMPACT Core+FIB and IMPACT Core+APTT are optimal for the 6-month unfavorable outcome and 6-month mortality, respectively (AUC, 0.830 and 0.878). The new models were built based on the regression coefficients of the models. Internal verification indicated that for the prediction of 6-month unfavorable outcome and 6-month mortality, both the IMPACT Core+FIB model and the IMPACT Core+APTT model show better discrimination (AUC, 0.823 vs. 0.818 and 0.853 vs. 0.837), better calibration (HL, p=0.114 and p=0.317) and higher precision (Brier score, 0.148 vs. 0.141 and 0.147 vs. 0.164), respectively, than the original models. Conclusion. Our research shows that the combination of the traumatic brain injury prognostic models and coagulation indices can improve the 6-month outcome prediction of patients with TBI.

With the increasing number of underground engineering construction projects such as coal mining, tunnel, and subway, water inrush disasters occur more and more frequently. Inspired by the phenomenon of microbial mineralization and diagenesis, microbial-induced calcium carbonate precipitation (MICP) is used to repair cracks in cement-based materials, which provides a new idea to solve the problem of water inrush. To investigate the self-healing properties of microbial capsules, this paper selected epoxy resin E-51 cured by DMP-30 as the wall material and Bacillus pasteurii as the core materials for experiments. In this paper, a single-factor method was adopted to determine the optimal preparation process of microbial capsules and the oil-phase separation method to prepare the microbial capsules. The effects of various factors on the experimental results under different core-wall ratios, reaction time, reaction temperatures, and agitation rates were analyzed. Microbial capsules were analyzed by Fourier transform infrared spectroscopy and optical microscopy to explore the functional groups and features of microbial capsules. The experimental results showed that the microbial capsules achieved the best performance with a core-to-wall ratio of 1 : 3, a reaction temperature of 50°C, a reaction time of 40 min, and a stirring rate of 300 rpm. Meanwhile, we determined the spore survival rate of microbial capsules and finally studied the waterproofness, storage stability, and rupture under the pressure of microbial capsules. We concluded that microbial capsules have high-efficiency and self-healing properties.

Microbial Induced Calcite Precipitation (MICP) is a biochemical process widely found in nature, also known as microbial mineralization. This paper investigates whether this process can help promote the intelligent reinforcement and repair of underground projects such as mines and tunnels. We selected Bacillus sphaericus and Bacillus mucilaginosus as the research objects. The former has an outstanding urease production ability, and the latter can secrete carbonic anhydrase in vitro. Bacillus mucilaginosus was introduced into the culture solution of Bacillus sphaericus in the most suitable culture environment, and the changes of mineralization rate and mineralization yield of Bacillus sphaericus were observed and analyzed. The results revealed that, to maintain the highest growth rate of Bacillus sphaericus, the optimal pH value was between 7 and 8, the optimal urea concentration was 0.5 mol/L, the optimal Ca2+ concentration was 0.6 mol/L, and the optimal Luria-Bertani (LB) culture concentration was 20 g/L. The amount of biomineralized calcium carbonate precipitated in the double bacteria solution can reach 1.89 times the amount of the precipitation in the Bacillus sphaericus solution under the same conditions. It concludes that the introduction of Bacillus mucilaginosus can effectively increase the mineralization yield of Bacillus sphaericus without affecting the mineralized products.

Background ‒ Both the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) and the Corticosteroid randomization after significant head injury (CRASH) models are globally acknowledged prognostic algorithms for assessing traumatic brain injury (TBI) outcomes. The aim of this study is to externalize the validation process and juxtapose the prognostic accuracy of the CRASH and IMPACT models in moderate-to-severe TBI patients in the Chinese population. Methods ‒ We conducted a retrospective study encompassing a cohort of 340 adult TBI patients (aged > 18 years), presenting with Glasgow Coma Scale (GCS) scores ranging from 3 to 12. The data were accrued over 2 years (2020–2022). The primary endpoints were 14-day mortality rates and 6- month Glasgow Outcome Scale (GOS) scores. Analytical metrics, including the area under the receiver operating characteristic curve for discrimination and the Brier score for predictive precision were employed to quantitatively evaluate the model performance. Results ‒ Mortality rates at the 14-day and 6-month intervals, as well as the 6-month unfavorable GOS outcomes, were established to be 22.06, 40.29, and 65.59%, respectively. The IMPACT models had area under the curves (AUCs) of 0.873, 0.912, and 0.927 for the 6-month unfavorable GOS outcomes, with respective Brier scores of 0.14, 0.12, and 0.11. On the other hand, the AUCs associated with the six-month mortality were 0.883, 0.909, and 0.912, and the corresponding Brier scores were 0.15, 0.14, and 0.13, respectively. The CRASH models exhibited AUCs of 0.862 and 0.878 for the 6-month adverse outcomes, with uniform Brier scores of 0.18. The 14-day mortality rates had AUCs of 0.867 and 0.87, and corresponding Brier scores of 0.21 and 0.22, respectively. Conclusion ‒ Both the CRASH and IMPACT algorithms offer reliable prognostic estimations for patients suffering from craniocerebral injuries. However, compared to the CRASH model, the IMPACT model has superior predictive accuracy, albeit at the cost of increased computational intricacy. [ABSTRACT FROM AUTHOR]