Performance of trauma scoring systems in predicting mortality in geriatric trauma patients: comparison of the ISS, TRISS, and GTOS based on a systemic review and meta-analysis.

PURPOSE: This meta-analysis aimed to evaluate the performance of the Injury Severity Score (ISS), Trauma and Injury Severity Score (TRISS), and the Geriatric Trauma Outcome Score (GTOS) in predicting mortality in geriatric trauma patients. METHODS: The MEDLINE, Web of Science, and EMBASE databases were searched for studies published from January 2008 to October 2023. Studies assessing the performance of the ISS, TRISS, or GTOS in predicting mortality in geriatric trauma patients (over 60 years old) and reporting data for the analysis of the pooled area under the receiver operating characteristic curve (AUROC) and the hierarchical summary receiver operating characteristic curve (HSROC) were included. Studies that were not conducted in a group of geriatric patients, did not consider mortality as the outcome variable, or had incomplete data were excluded. The Critical Appraisal Skills Programme (CASP) Clinical Prediction Rule Checklist was utilized to assess the risk of bias in included studies. STATA 16.0. was used for the AUROC analysis and HSROC analysis. RESULTS: Nineteen studies involving 118,761 geriatric trauma patients were included. The pooled AUROC of the TRISS (AUC = 0.82, 95% CI: 0.77-0.87) was higher than ISS (AUC = 0.74, 95% CI: 0.71-0.79) and GTOS (AUC = 0.80, 95%CI: 0.77-0.83). The diagnostic odds ratio (DOR) calculated from HSROC curves also suggested that the TRISS (DOR = 21.5) had a better performance in predicting mortality in geriatric trauma patients than the ISS (DOR = 6.27) and GTOS (DOR = 4.76). CONCLUSION: This meta-analysis suggested that the TRISS showed better accuracy and performance in predicting mortality in geriatric trauma patients than the ISS and GTOS.

Paper-based ratiometric fluorescent sensing platform based on mixed quantum dots for the detection of glucose in urine.

A paper-based ratiometric fluorescent sensing platform has been developed for glucose detection based on a dual-emission fluorescent probe consisting of carbon quantum dots (C QDs) and CdTe QDs. When the two kinds of QDs are mixed, the fluorescence of C QDs is reversibly quenched by CdTe QDs. However, in the presence of glucose, the fluorescence of CdTe QDs is quenched by H2O2 catalyzed by glucose oxidase (GOx), which restores the fluorescence of C QDs. The proposed paper-based ratiometric fluorescent sensing platform exhibited good sensitivity and selectivity towards glucose. The working linear range was 0.1 mM to 50 mM with a limit of detection (LOD) of 0.026 mM. Additionally, the proposed paper-based sensor possesses viability for the determination of glucose in actual urine samples.

Recent Progress in Porphyrin/g-C3N4 Composite Photocatalysts for Solar Energy Utilization and Conversion.

Transforming solar energy into chemical bonds is a promising and viable way to store solar energy. Porphyrins are natural light-capturing antennas, and graphitic carbon nitride (g-C3N4) is an effective, artificially synthesized organic semiconductor. Their excellent complementarity has led to a growing number of research papers on porphyrin/g-C3N4 hybrids for solar energy utilization. This review highlights the recent progress in porphyrin/g-C3N4 composites, including: (1) porphyrin molecules/g-C3N4 composite photocatalysts connected via noncovalent or covalent interactions, and (2) porphyrin-based nanomaterials/g-C3N4 composite photocatalysts, such as porphyrin-based MOF/g-C3N4, porphyrin-based COF/g-C3N4, and porphyrin-based assembly/g-C3N4 heterojunction nanostructures. Additionally, the review discusses the versatile applications of these composites, including artificial photosynthesis for hydrogen evolution, CO2 reduction, and pollutant degradation. Lastly, critical summaries and perspectives on the challenges and future directions in this field are also provided.

Single-site bipyridine cobalt complexes covalently embedded into graphitic carbon nitride with excellent photocatalytic activity and selectivity towards CO2 reduction.

A combination of a semiconductor-based photosensitizer with molecular catalysts via covalent bonds is an effective way to utilize solar energy to reduce CO2 into value-added chemicals with high efficiency and selectivity. In this study, 2,2'-bpy-5,5'-dialdehyde functioned as organic ligands and were embedded into the skeleton of g-CN through imine bonds via thermal copolymerization. The introduction of 2,2'-bpy can not only chelate with earth-abundant Co as single-site catalytic centers but also can optimize the properties of original g-CN such as the enlarged specific surface area and extended visible light absorption range. The CO evolution rate of g-CN-bpy-Co can reach up to 106.3 µmol g-1 h-1 with a selectivity of 97% over proton reduction, which was 82-fold than that of g-CN-Co. The different coordination environments and valence states of cobalt were also studied simultaneously and the results showed that Co(II) exhibited superior catalytic activity towards Co(III). Control experiments demonstrated that the covalent linkage between g-CN and Co-2,2'-bpy plays a vital role in photocatalytic activity and selectivity. Besides, the CO generation rate demonstrated linear growth upon visible light irradiation up to 72 h and preferable recyclability. This research provides a new facile way to fabricate low-priced photocatalysts with high activity and selectivity and bridge homogeneous and heterogeneous catalysis.

Poly(divinylbenzene) as a fiber coating for headspace solid-phase microextraction of polycyclic aromatic hydrocarbons from river water.

Porous polydivinylbenzene microspheres with high specific surface area were prepared by distillation-precipitation polymerization, and were used as the coating material in headspace solid phase microextraction for extracting polycyclic aromatic hydrocarbons. Compared with the other reported sorbents, PDVB exhibits lower cost and higher extraction efficiency, and the enrichment factors can reach 5963-16 720.

Research on Classification of Open-Pit Mineral Exploiting Information Based on OOB RFE Feature Optimization.

Mineral exploiting information is an important indicator to reflect regional mineral activities. Accurate extraction of this information is essential to mineral management and environmental protection. In recent years, there are an increasingly large number of pieces of research on land surface information classification by conducting multi-source remote sensing data. However, in order to achieve the best classification result, how to select the optimal feature combination is the key issue. This study creatively combines Out of Bag data with Recursive Feature Elimination (OOB RFE) to optimize the feature combination of the mineral exploiting information of non-metallic building materials in Fujian province, China. We acquired and integrated Ziyuan-1-02D (ZY-1-02D) hyperspectral imagery, landsat-8 multispectral imagery, and Sentinel-1 Synthetic Aperture Radar (SAR) imagery to gain spectrum, heat, polarization, and texture features; also, two machine learning methods were adopted to classify the mineral exploiting information in our study area. After assessment and comparison on accuracy, it proves that the classification generated from our new OOB RFE method, which combine with random forest (RF), can achieve the highest overall accuracy 93.64% (with a kappa coefficient of 0.926). Comparing with Recursive Feature Elimination (RFE) alone, OOB REF can precisely filter the feature combination and lead to optimal result. Under the same feature scheme, RF is effective on classifying the mineral exploiting information of the research field. The feature optimization method and optimal feature combination proposed in our study can provide technical support and theoretical reference for extraction and classification of mineral exploiting information applied in other regions.

Correlation between the microbial community and ethyl carbamate generated during Huzhou rice wine fermentation.

Ethyl carbamate (EC) is a potential carcinogen that is mainly produced by the spontaneous reaction between urea and ethanol during rice wine brewing. Huzhou rice wine (HZRW) is a traditional Chinese rice wine, but the correlation between its urea content and the microbial communities present during the fermentation process has not yet been evaluated. In this study, high-throughput sequencing technology was used to monitor the microbial community composition of HZRW in the different fermentation stages. The correlations between the microbial community and the physical and chemical properties and EC, urea and arginine contents were evaluated using the redundancy analysis (RDA) method. The metabolic profiles of key genes in the arginine and urea metabolic pathways were obtained via phylogenetic investigation of the communities by reconstruction of unobserved states (PICRUSt). The results showed that the fungal genera Saccharomyces, Issatchenkia, Torulaspora and Rhizopus were dominant during the fermentation of HZRW. Weissella and Acinetobacter were the dominant bacterial genera in the early stage, while Weissella, Staphylococcus, Leuconostoc and Streptophyta were the dominant bacterial genera in the late stage. Urea and arginine were positively correlated with Saccharomyces, Lactobacillus and Staphylococcus. In addition, the dominant genera of both fungi and bacteria were involved in the metabolism of arginine and urea. Finally, the relationships between the dominant microorganisms and key genes of the arginine and urea metabolic pathways were established. The obtained results are helpful in better understanding the mechanisms of metabolism of arginine and urea during rice wine fermentation and therefore improving the safety profile of rice wine.

The microbiome of Chinese rice wine (Huangjiu).

Chinese rice wine (Huangjiu) has a long history and has been popular in China for thousands of years. During Huangjiu fermentation, many kinds of microorganisms are involved and hundreds of metabolites are produced, which form its unique aroma. The composition of the Huangjiu microbiome has a strong influence on the flavor and quality of the final consumer product. Therefore, this review summarizes the research progress on the main components, quality control indicators and flavor compounds, as well as potential hazards during the fermentation of Huangjiu. The influence of the dominant microbial species on the Huangjiu fermentation, the sensory qualities and the formation of harmful substances are discussed. This helps to provide a theoretical basis for modification of the Huangjiu microbiome to improve control of the fermentation process and the overall sensory quality of the final product.

Preparation of multivariate zirconia metal-organic frameworks for highly efficient adsorption of endocrine disrupting compounds.

Owing to their structural and functional tunability, the preparation of multivariate metal-organic frameworks (MTV-MOFs) and investigation of their potential application has become a hot topic in fields of environment and energy. To achieve more adsorption and removal performance, a series of multivariate Zr-MOFs (TCPP@MOF-808s) were prepared via mixed-ligands strategy for the first time. The morphology, as well as adsorption and removal properties of TCPP@MOF-808s can be controlled by adjusting ratio of the linkers. 57%TCPP@MOF-808 could provide ideal appearance with excellent stability. By using 57%TCPP@MOF-808 as sorbent, a dispersive solid-phase extraction (dSPE) was developed for extraction of endocrine disrupting compounds (EDCs) including BPA, 17ß-E2, 17α-E2, E1, and HEX from environmental water prior to HPLC analysis. The pseudo-second-order model can describe the adsorption kinetic data well. Using Langmuir isotherm model, the maximum adsorption capacities of BPA, 17ß-E2, 17α-E2, and E1 were calculated as 94.34, 104.17, 109.89, and 121.95 mg·g-1, respectively. The LODs for the analysis of EDCs with HPLC-DAD by using 57%TCPP@MOF-808 as sorbent were achieved in the range of 0.01-0.03 ng·mL-1. The recoveries were obtained in the range of 74.63-98.00%. Enrichment factors were calculated in the range of 146-312. This work provides an effective strategy for design and preparation of multifunctional nanomaterials to improve their potential applications in the detection of environmental pollutants.

Lithological information extraction and classification in hyperspectral remote sensing data using Backpropagation Neural Network.

The purposes are to solve the isomorphism encountered while processing hyperspectral remote sensing data and improve the accuracy of hyperspectral remote sensing data in extracting and classifying lithological information. Taking rocks as the research object, Backpropagation Neural Network (BPNN) is introduced. After the hyperspectral image data are normalized, the lithological spectrum and spatial information are the feature extraction targets to construct a deep learning-based lithological information extraction model. The performance of the model is analyzed using specific instance data. Results demonstrate that the overall accuracy and the Kappa coefficient of the lithological information extraction and classification model based on deep learning were 90.58% and 0.8676, respectively. This model can precisely distinguish the properties of rock masses and provide better performance compared with the state of other analysis models. After introducing deep learning, the recognition accuracy and the Kappa coefficient of the proposed BPNN model increased by 8.5% and 0.12, respectively, compared with the traditional BPNN. The proposed extraction and classification model can provide some research values and practical significances for the hyperspectral rock and mineral classification.

Fabrication of stable multivariate metal-organic frameworks with excellent adsorption performance toward bisphenols from environmental samples.

As a type of environmental endocrine disrupting chemicals, bisphenols (BPs) have a certain embryonic toxicity and teratogenicity, which can significantly increase the risks of breast cancer, prostate cancer, leukemia and other cancers. In this work, stable multivariate metal-organic frameworks (UiO-66-NH2/TCPPx) were synthesized via in situ one-pot method and used as miniaturized dispersive solid-phase extraction (dµSPE) sorbents for extraction of trace BPs from environmental samples. The phase purity, crystal morphology and physical properties of UiO-66-NH2/TCPPx samples were varied by adjusting the mass ratio of TCPP. The extraction performance of UiO-66-NH2/TCPPx samples were investigated and UiO-66-NH2/TCPP1.0 exhibited the highest adsorption efficiency. Besides, UiO-66-NH2/TCPP1.0 possessed excellent recycling stability for the adsorption and desorption of BPs more than 20 cycles. The experimental parameters including amount of adsorbent, adsorption time, sample solution pH, temperature, desorption time and desorption solvents which affecting the efficiency of dµSPE were studied, respectively. Good linearity (R2 > 0.9992) in range of 0.1-200 ng mL-1 was obtained. The detection limits (S/N = 3) and quantification limits (S/N = 10) were achieved at 0.03-0.08 ng mL-1 and 0.1-0.5 ng mL-1, respectively. The relative standard deviations (RSDs) of intra-day and inter-day ranged from 2.5 to 5.5% and 1.1-6.8%. Enrichment factors were calculated in the range of 303-338. The obtained recoveries of bisphenol F (BPF), bisphenol A (BPA), bisphenol B (BPB) and bisphenol AF (BPAF) were 81.26-91.03% (RSDs = 0.96-6.47%), 82.2-97.27% (RSDs = 0.45-6.15%), 87.56-97.26% (RSDs = 1.1-6.22%) and 82.2-100.8% (RSDs = 0.46-4.07%). The UiO-66-NH2/TCPP1.0 can be employed as potential dµSPE sorbents for the enrichment of trace BPs in the environmental samples.

Construction and Validation of a Novel Ferroptosis-Related Prognostic Model for Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a clonal malignant proliferative blood disorder with a poor prognosis. Ferroptosis, a novel form of programmed cell death, holds great promise for oncology treatment, and has been demonstrated to interfere with the development of various diseases. A range of genes are involved in regulating ferroptosis and can serve as markers of it. Nevertheless, the prognostic significance of these genes in AML remains poorly understood. Transcriptomic and clinical data for AML patients were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Univariate Cox analysis was performed to identify ferroptosis-related genes with prognostic value, and the least absolute shrinkage and selection operator (LASSO) algorithm and stepwise multivariate Cox regression analysis were utilized to optimize gene selection from the TCGA cohort (132 samples) for model construction. Tumor samples from the GEO database (136 samples and 104 samples) were used as validation groups to estimate the predictive performance of the risk model. Finally, an eight-gene prognostic signature (including CHAC1, CISD1, DPP4, GPX4, AIFM2, SQLE, PGD, and ACSF2) was identified for the prediction of survival probability and was used to stratify AML patients into high- and low-risk groups. Survival analysis illustrated significantly prolonged overall survival and lower mortality in the low-risk group. The area under the receiver operating characteristic curve demonstrated good results for the training set (1-year: 0.846, 2-years: 0.826, and 3-years: 0.837), which verified the accuracy of the model for predicting patient survival. Independent prognostic analysis indicated that the model could be used as a prognostic factor (p ≤ 0.001). Functional enrichment analyses revealed underlying mechanisms and notable differences in the immune status of the two risk groups. In brief, we conducted and validated a novel ferroptosis-related prognostic model for outcome prediction and risk stratification in AML, with great potential to guide individualized treatment strategies in the future.

Enhancement of 2-phenylethanol production by a wild-type Wickerhamomyces anomalus strain isolated from rice wine.

2-Phenylethanol (2-PE) is an important high-grade aromatic alcohol, which is widely used in the cosmetics, perfumery and food industries. However, 2-PE is mainly synthesized using a chemical route, which produces environmental pollution and harmful by-products. Screening of high-yielding wild-type strains has become an important goal for the future biosynthesis of 2-PE. In this study, a wild-type Wickerhamomyces anomalus was isolated from rice wine fermented mash. By optimizing the initial glucose and l-phenylalanine concentrations, 2630.7 mg/L of 2-PE was obtained in shaking flasks. The conditions of initial glucose and l-phenylalanine concentration, pH, and inoculation amount were optimized for 2-PE production with W. anomalus. Finally, based on the optimal conditions, the 2-PE titer reached 4,727.3 mg/L by a single-dose fed-batch strategy in a 5-L bioreactor. The results showed that the ability was expanded to harness the Ehrlich pathway for the production of high-value aromatics in aroma-producing yeast species.

Preparation of Al-doped mesoporous crystalline material-41 as fiber coating material for headspace solid-phase microextraction of polycyclic aromatic hydrocarbons from human urine.

The Al-doped mesoporous crystalline material-41 (Al-MCM-41) composite was prepared and applied as fiber coating material of headspace solid-phase microextraction (HS-SPME) for extraction of polycyclic aromatic hydrocarbons (PAHs) from human urine. Five PAHs including acenaphthene, fluorene, phenanthrene, anthracene, and pyrene are chosen as target analytes to evaluate the performance of the material by GC-FID analysis. The mesoporous Al-MCM-41 composite was characterized by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, nitrogen adsorption/desorption measurement, and thermogravimetric analysis. The parameters affecting the extraction efficiency of HS-SPME were investigated. Under the optimal conditions, the method exhibits ideal linearity for target analytes in the range of 0.3-600 ng⋅mL-1 with the coefficients (R2) equal or higher than 0.9906. The enrichment factors are calculated from 540 to 1760. The limits of detection (LODs) and limits of quantitation (LOQs) are between the ranges of 0.06-0.18 and 0.3-0.9 ng⋅mL-1, respectively. The relative standard deviations (RSDs) (n = 5) of intra-day and inter-day are in the ranges of 1.08-7.49% and 2.84-18.3% respectively. The fiber-to-fiber reproducibility (n = 3) is in the range of 6.47-13.9%. The method was successfully applied for the analysis of PAHs in human urine with reasonable recoveries which is ranging from 73.29 to 116.1%.

Platinum-Copper Bimetallic Alloy Nanoflowers as Efficient Electrocatalyst for the Methanol Oxidation Reaction.

Special morphological noble metal-based bimetallic alloy nanostructures became popular for methanol oxidation reaction in order to reduce the high cost of the Pt catalyst and improve the catalyst activity. Herein, we developed a facile one pot hydrothermal method for the synthesis of platinum-copper bimetallic nanoflowers (Pt-Cu NFs) in the presence of hexadecyl trimethyl ammonium bromide (CTAB). The morphology, structure and composition of Pt-Cu NFs were carefully characterized and the synthesized parameters were optimized systematically by adjusting different experimental conditions. Results showed that the CTAB usage and the NaI amount were critical to the controlled synthesis of Pt-Cu NFs. The Pt-Cu NFs were high-performance electrocatalysts for the methanol oxidation reaction (MOR) with superior activity and superior stability in alkaline solution, which were far better than pure Pt nanoparticle electrocatalysts.

High-level expression and characterization of solvent-tolerant lipase.

In this study, the coding sequence of the lipase from Proteus sp. SW1 was optimized via codon optimization and subjected to expression in Pichia pastoris GS115. The maximum enzyme yield was 387 mg/L in the supernatants of the shake-flask culture. The purified recombinant lipase exhibited a specific activity of 130 U/mg toward p-nitrophenyl Laurate. Its optimum pH and temperature were 8.0 and 40°C, respectively. It was highly stable and even activated in water-miscible solvents, showing over 102% residual activity after 24 h incubation in ethanol, acetone, isopropanol and acetonitrile. In addition, the enzyme showed promoted activity with the increasing concentrations of methanol/ethanol and exhibited the maximum activity at 80%. In a solvent-free system for biodiesel synthesis with a one-step addition of methanol, the recombinant lipase displayed a 87% conversion rate toward palm oil at the high water content of 80%. The highly improved expression level and activity of the recombinant lipase may contribute to enable its commercial-scale production, and the unique properties would make it a particularly promising biocatalyst for biodiesel production in the future.

Highly Efficient, Rapid, and Simultaneous Removal of Cationic Dyes from Aqueous Solution Using Monodispersed Mesoporous Silica Nanoparticles as the Adsorbent.

In this work, a highly efficient and rapid method for simultaneously removing cationic dyes from aqueous solutions was developed by using monodispersed mesoporous silica nanoparticles (MSNs) as the adsorbents. The MSNs were prepared by a facile one-pot method and characterized by scanning electron microscopy, transmission electron microscopy, Fourier-transform infrared spectroscopy, and Brunauer-Emmett-Teller. Experimental results demonstrated that the as-prepared MSNs possessed a large specific surface area (about 585 m²/g), uniform particle size (about 30 nm), large pore volume (1.175 cm³/g), and narrow pore size distribution (1.68 nm). The materials showed highly efficient and rapid adsorption properties for cationic dyes including rhodamine B, methylene blue, methyl violet, malachite green, and basic fuchsin. Under the optimized conditions, the maximum adsorption capacities for the above mentioned cationic dyes were in the range of 14.70 mg/g to 34.23 mg/g, which could be achieved within 2 to 6 min. The probable adsorption mechanism of MSNs for adsorption of cationic dyes is proposed. It could be considered that the adsorption is mainly controlled by electrostatic interactions and hydrogen bonding between the cationic dyes and MSNs. As a low-cost, biocompatible, and environmentally friendly material, MSNs have a potential application in wastewater treatment for removing some environmental cationic contaminants.

High-Throughput Development of SSR Markers from Pea (Pisum sativum L.) Based on Next Generation Sequencing of a Purified Chinese Commercial Variety.

Pea (Pisum sativum L.) is an important food legume globally, and is the plant species that J.G. Mendel used to lay the foundation of modern genetics. However, genomics resources of pea are limited comparing to other crop species. Application of marker assisted selection (MAS) in pea breeding has lagged behind many other crops. Development of a large number of novel and reliable SSR (simple sequence repeat) or microsatellite markers will help both basic and applied genomics research of this crop. The Illumina HiSeq 2500 System was used to uncover 8,899 putative SSR containing sequences, and 3,275 non-redundant primers were designed to amplify these SSRs. Among the 1,644 SSRs that were randomly selected for primer validation, 841 yielded reliable amplifications of detectable polymorphisms among 24 genotypes of cultivated pea (Pisum sativum L.) and wild relatives (P. fulvum Sm.) originated from diverse geographical locations. The dataset indicated that the allele number per locus ranged from 2 to 10, and that the polymorphism information content (PIC) ranged from 0.08 to 0.82 with an average of 0.38. These 1,644 novel SSR markers were also tested for polymorphism between genotypes G0003973 and G0005527. Finally, 33 polymorphic SSR markers were anchored on the genetic linkage map of G0003973 × G0005527 F2 population.

Wrapping DNA-gated mesoporous silica nanoparticles for quantitative monitoring of telomerase activity with glucometer readout.

This work reports a simple and sensitive sensing protocol for the quantitative monitoring of telomerase activity based on target-responsive release of cargo from wrapping DNA-capped mesoporous silica nanoparticles (MSNs) by coupling with a portable personal glucometer (PGM). To construct such an assay system, glucose molecules are initially loaded into the pores of the aminated MSN, and the pores are then sealed with a specially designed wrapping DNA. Upon the addition of telomerase and dNTPs, the assembled wrapping DNA strands are prolonged with the assistance of telomerase on the aminated MSN. Accompanying the progression of telomerase, the extended DNA strands detach from the MSN, owing to the formation of rigid, hairpin-like DNA structures. The "molecular gates" are then opened, resulting in the release of glucose from MSN. The released glucose molecules can be quantitatively monitored using an external PGM. The PGM signal increases with the increment of telomerase activity. Under optimal conditions, the PGM-based sensing platform exhibits good analytical properties for the determination of telomerase activity and allows for the detection of telomerase activity in the HeLa extract at concentrations as low as 80 cells mL-1. Using somatic and tumor cell lines, the generality of the assay is evaluated with satisfactory results. The inhibition effect of 3'-azido-3'-deoxythymidine also receives a good performance in the telomerase-inhibitor screening research. The methodology affords good reproducibility and simple operations, thus providing a useful scheme for practical use in a quantitative telomerase activity assay for clinical application.

Protective effect of etomidate on spinal cord ischemia-reperfusion injury induced by aortic occlusion in rabbits.

BACKGROUND: We conducted a randomized controlled study on the neuroprotective effect of a commonly used anesthetic, etomidate, in an ischemia-reperfusion (IR) injury rabbit model. METHODS: We studied 24 white adult Japanese rabbits at the animal facility at the Medical College of Wuhan University. Rabbits were randomly assigned into a sham-operation group (group I), an IR group (group II), and an etomidate-treated IR group (group III). Rabbits in groups II and III were subjected to 45 min of infrarenal aortic cross-clamping to induce spinal cord ischemia, while group I rabbits received the sham operation as a control. Following an initial single-dose intravenous injection at 0.6 mg/kg 10 min before aortic clamping, etomidate was infused intravenously at 3mg/(kg . hr) in group III rabbits until unclamping, while 0.9% saline was given as the control in group II. RESULTS: Changes in neurological function scores, histopathology, electromyography, malondialdehyde levels, superoxide dismutase activities, and the concentrations of Ca(2+), Mg(2+), Cu(2+), and Zn(2+) ions were measured. Compared with the sham-operation group, group II showed significant IR injury-associated changes in all parameters evaluated (p<0.01), whereas these unfavorable changes were significantly reversed in etomidate-treated animals (p<0.05 or p<0.01). No significant differences were observed between group I and group III animals in all parameters. CONCLUSION: Etomidate displayed a potent neuroprotective effect against IR-induced spinal cord injuries. We propose that this effect may be associated with the ability of etomidate to enhance the activities of endogenous antioxidants and maintain the ion balance in IR-affected tissues.