H2S is involved in drought-mediated stomatal closure through PLDα1 in Arabidopsis.

MAIN CONCLUSION: PLDα1 promoted H2S production by positively regulating the expression of LCD. Stomatal closure promoted by PLDα1 required the accumulation of H2S under drought stress. Phospholipase Dα1 (PLDα1) acting as one of the signal enzymes can respond to drought stress. It is well known that hydrogen sulfide (H2S) plays an important role in plant responding to biotic or abiotic stress. In this study, the functions and relationship between PLDα1 and H2S in drought stress resistance in Arabidopsis were explored. Our results indicated that drought stress promotes PLDα1 and H2S production by inducing the expression of PLDα1 and LCD genes. PLDα1 and LCD enhanced plant tolerance to drought by regulating membrane lipid peroxidation, proline accumulation, H2O2 content and stomatal closure. Under drought stress, the H2O2 content of PLDα1-deficient mutant (pldα1), L-cysteine desulfhydrase (LCD)-deficient mutant (lcd) was higher than that of ecotype (WT), the stomatal aperture of pldα1 and lcd was larger than that of WT. The transcriptional and translational levels of LCD were lower in pldα1 than that in WT. Exogenous application of the H2S donor NaHS or GYY reduced the stomatal aperture of WT, pldα1, PLDα1-CO, and PLDα1-OE lines, while exogenous application of the H2S scavenger hypotaurine (HT) increased the stomatal aperture. qRT-PCR analysis of stomatal movement-related genes showed that the expression of CAX1, ABCG5, SCAB1, and SLAC1 genes in pldα1 and lcd were down-regulated, while ACA1 and OST1 gene expression was significantly up-regulated. Thus, PLDα1 and LCD are required for stomatal closure to improve drought stress tolerance.

Delineating molecular regulatory network of meat quality of longissimus dorsi indicated by transcriptomic, proteomic, and metabolomics analysis in rabbit.

This study aims to investigate the potential regulatory network responsible for the meat quality using multi-omics to help developing better varieties. Slaughter performance and meat quality of Shuxing No.1 rabbit outperformed IRA rabbit according to the tested rabbit parameters. Differentially expressed genes (DEGs) and differentially abundance proteins (DAPs) were involved in meat quality-related pathways, such as PI3K - Akt and MAPK signaling pathways. Only SMTNL1 and PM20D2 shared between DEGs and DAPs. Olfactory-sensitive undecanal, a differentially abundant metabolite (DAM) in volatilomics (vDAMs), correlated with all of the remaining 11 vDAMs, and most of 12 vDAMs were associated with amino acid metabolism. Integration revealed that 829 DEGs/DAPs were associated with 15 DAMs in four KEGG pathways, such as melatonin (a DAM in widely targeted metabolomics) was significantly positively correlated with ALDH and negatively correlated with RAB3D and CAT in the tryptophan metabolism pathway. This study sheds light on the potential mechanisms that contribute to the improved meat quality and flavor. SIGNIFICANCE: Shuxing No.1 rabbit is a new breed of meat rabbit in the Chinese market. In meat marketing, meat quality usually determines the purchase intention of consumers. Determining the biological and molecular mechanisms of meat quality in meat rabbit is essential for developing strategies to improve meat quality. According to the tested rabbit parameters, this study ascertained that the slaughter performance and meat quality of Shuxing No.1 rabbit surpasses that of IRA rabbit. The present study profiled the transcriptome, proteome, widely targeted metabolome, and volatilome of longissimus dorsi from Shuxing No.1 rabbit and IRA rabbit. The study found that meat quality and flavor-related tryptophan metabolism pathway is enriched with many DEGs/DAPs (including ALDH, RAB3D, and CAT), as well as a DAM, melatonin. This study sheds light on the potential mechanisms that contribute to the improved meat quality and flavor.

Data-driven sustainability evaluation and manufacturing system enhancement from economic, environmental, social, and sustainability perspectives.

Sustainable manufacturing is crucial to achieving carbon neutrality targets. However, research on the sustainability of manufacturing systems is limited, and high consumption, low efficiency, and high emissions have resulted in high resource consumption and rapid environmental degradation. Therefore, it is of great importance to establish an evaluation and improvement indicator system conducive to sustainable development. To this end, this study developed a data-driven methodology for evaluating and enhancing the sustainability of manufacturing systems. Manufacturing system production process data, with data dimensions unified via the emergy method, were used to construct a sustainable development evaluation model that includes four perspectives: economy, environment, society, and sustainability. The model was applied to a flange production workshop in China to analyze the interrelation mechanisms among energy consumption, resource consumption, and environmental pollution, and identify optimization schemes to improve sustainability. After implementing these optimization schemes, the emergy yield rate (EYR) of the flange increased by 23.40%, the environmental load rate (ELR) decreased by 19.03%, the per capita emergy (EPP) increased by 6.88%, and the emergy-based sustainability index (ESI) increased by 52.76%. The method presented herein offers a novel and effective tool to analyze and visualize sustainable development in manufacturing systems and identify the relationship between technology and management in the manufacturing industry; however, this method is based on historical data and rules, and lacks of flexible response to unknown situations. The results provide a reference for enterprises to achieve sustainable and lean manufacturing.

Data-driven low-carbon transformation management for manufacturing enterprises: an eco-efficiency perspective.

The low-carbon transformation of manufacturing enterprises is considered to be imperative to achieve carbon neutrality. Therefore, we propose a data-driven strategy to achieve a low-carbon transformation of manufacturing enterprises from an eco-efficiency perspective. Following the collection of input (energy, materials, equipment, R&D, and services) and output (waste and products) data from production systems of manufacturing enterprises, an ecological efficiency model of manufacturing enterprise production system was constructed from the perspective of carbon emissions, thus allowing the quantitative evaluation of the ecological efficiency of the production system. Furthermore, a "measurable, evaluable, and optimized" low-carbon transformation and upgrading method for manufacturing enterprise production system was established. Finally, through the production practice data of an enterprise from 2017 to 2021, the feasibility and effectiveness of this method were verified. The results show that this method can effectively improve the ecological efficiency of enterprises by 3.6% and reduce waste emissions by 12%. Our study provides new tools for improving the ecological efficiency of manufacturing systems, along with theoretical and methodological support to manufacturing enterprises for low-carbon transformation.

PLDδ, auxin, and H2O2 mediated the allelopathic effect of cycloastragenol on root growth in Arabidopsis.

Cycloastragenol (CAG) is a tetra-cyclic triterpenoid allelochemical. It has been widely studied in animals but rarely in plants. Here, we reported that a model allelochemical CAG inhibited primary root elongation of Arabidopsis by reducing the sizes of both the meristem and elongation zones. Phospholipase Dδ(PLDδ), hydrogen peroxide (H2O2), and auxin affected this process. After treatment with CAG, the expression of PLDδ and the activity of the Phospholipase D(PLD) enzyme increased in WT. Mutants analysis demonstrated that PLDδ negatively regulated the primary root elongation by CAG treatment. CAG treatment stimulated the accumulation of H2O2 in roots. The production of H2O2 was derived from cell wall peroxidase. Mutants analysis showed that PLDδ positively regulated the production of H2O2 by CAG treatment. CAG also decreased auxin content in the root tip by affecting the expression of auxin synthesis-related genes. PLDδ was involved in the auxin reduction mediated by CAG, but H2O2 did not participate in this process. In conclusion, PLDδ, auxin, and H2O2 mediated the inhibition of primary root growth by CAG in Arabidopsis.

Emergy-based sustainability measurement and evaluation of industrial production systems.

The sustainability of industrial production systems is considered to be the key to promoting green transformation and upgrading of manufacturing industry. This study proposes an emergy-based method for the measurement and evaluation of the sustainability of industrial production systems. The method uses emergy as a measure, expresses all types of inputs and outputs of production systems in terms of solar emergy, and constructs indicators for the sustainable evaluation of industrial production systems that account for economic and environmental benefits from the perspectives of system functions, ecology, and sustainability. This method was applied to a disc cam machining system at a machinery company, where the user was able to quantify the sustainability of the production system and, through feedback, optimise the production process to reduce energy consumption and environmental pollution and improve the sustainability of the production process. The results show that after optimization, the emergy yield ratio of the disc cam machining system is increased from 1.45 to 4.32, the environmental load ratio is reduced by 16%, and the emergy-based sustainability index is increased by 85%. The system has long-term sustainable development capability in the future. This study provides a new theoretical perspective on sustainability assessments of industrial production systems, and our findings provide a scientific basis for guiding the sound operation and sustainable development of industrial production systems.

A data-driven approach for the measurement and improvement of regional industrial ecological efficiency for carbon peaking and carbon neutralization.

Industrial ecological efficiency is regarded as an urgent challenge that affects the development of ecological civilization and environmental governance. Here, we propose a data-driven approach to measure and promote regional industrial ecological efficiency. We collected data related to regional industrial development and used the Data Envelopment Analysis-Banker Charnes and Cooper (DEA-BCC) model to measure regional industrial ecological efficiency from a static perspective. The Malmquist index model was then used to measure regional industrial ecological efficiency from a dynamic perspective. In addition, we used a Tobit regression model to identify the factors affecting regional industrial ecological efficiency. Through a case study of regional industrial ecological efficiency, we demonstrate the specific application of the proposed data-driven approach. This study provides a new and effective tool for improving industrial ecological efficiency at a regional scale. This method can help enterprises and local governments improve industrial ecological efficiency, coordinate the relationship between industrial economic growth and the ecological environment, and boost regional efforts to achieve carbon peaking and carbon neutralization goals.

Trait Analysis in Domestic Rabbits (Oryctolagus cuniculus f. domesticus) Using SNP Markers from Genotyping-by-Sequencing Data.

The domestic rabbit (Oryctolagus cuniculus f. domesticus) is a very important variety in biomedical research and agricultural animal breeding. Due to the different geographical areas in which rabbit breeds originated, and the long history of domestication/artificial breeding, rabbits have experienced strong selection pressure, which has shaped many traits of most rabbit varieties, such as color and weight. An efficient genome-wide single-nucleotide polymorphism (SNP) detection strategy is genotyping-by-sequencing (GBS), which has been widely used in many organisms. This study attempted to explore bi-allelic SNPs associated with fur color and weight-related traits using GBS in five rabbit breeds. The data consisted of a total 831,035 SNPs in 150 individuals from Californian rabbits (CF), German Zika rabbits (ZK), Qixing rabbits (QX), Sichuan grey rabbits (SG), and Sichuan white rabbits (SW). In addition, these five breeds of rabbits were obviously independent populations, with high genetic differentiation among breeds and low genetic diversity within breeds. A total of 32,144 SNP sites were identified by selective sweep among the different varieties. The genes that carried SNP loci in these selected regions were related to important traits (fur color and weight) and signal pathways, such as the MAPK/ERK signaling pathway and the Hippo signaling pathway. In addition, genes related to fur color and weight were identified, such as ASIPs, MITFs and KITs, ADCY3s, YAPs, FASs, and ACSL5s, and they had more SNP sites. The research offers the foundation for further exploration of molecular genetic markers of SNPs that are related to traits.

Genome-Wide Association Studies for Growth Curves in Meat Rabbits Through the Single-Step Nonlinear Mixed Model.

Growth is a complex trait with moderate to high heritability in livestock and must be described by the longitudinal data measured over multiple time points. Therefore, the used phenotype in genome-wide association studies (GWAS) of growth traits could be either the measures at the preselected time point or the fitted parameters of whole growth trajectory. A promising alternative approach was recently proposed that combined the fitting of growth curves and estimation of single-nucleotide polymorphism (SNP) effects into single-step nonlinear mixed model (NMM). In this study, we collected the body weights at 35, 42, 49, 56, 63, 70, and 84 days of age for 401 animals in a crossbred population of meat rabbits and compared five fitting models of growth curves (Logistic, Gompertz, Brody, Von Bertalanffy, and Richards). The logistic model was preferably selected and subjected to GWAS using the approach of single-step NMM, which was based on 87,704 genome-wide SNPs. A total of 45 significant SNPs distributed on five chromosomes were found to simultaneously affect the two growth parameters of mature weight (A) and maturity rate (K). However, no SNP was found to be independently associated with either A or K. Seven positional genes, including KCNIP4, GBA3, PPARGC1A, LDB2, SHISA3, GNA13, and FGF10, were suggested to be candidates affecting growth performances in meat rabbits. To the best of our knowledge, this is the first report of GWAS based on single-step NMM for longitudinal traits in rabbits, which also revealed the genetic architecture of growth traits that are helpful in implementing genome selection.

Decoupling of wastewater eco-environmental damage and China's economic development.

Wastewater pollution has been considered as a prominent bottleneck restricting global sustainable development. China is one of the largest discharges and eco-environmental damages of wastewater in the world. Through analyzing wastewater discharge data using emergy method in China from 2011 to 2017, the wastewater eco-environmental damage of 31 provinces is calculated with GDP and area to reveal the fundamental origins of inflection point of wastewater discharge in China. Studies results show that, (i) Chinese "12th Five-Year Plan" (2011-2015) is a watershed in wastewater discharge, and the eco-environment damages caused by China's wastewater accounted for more than 1/4 of GDP; (ii) China has the great potential to reduce eco-environment damages of 1.73 trillion $/year; (iii) In 2016 and 2017, wastewater eco-environmental damage has decreased by about 50% compared with that in 2015, and the effect of government policies was remarkable. We conclude that decoupling of China's economic development form eco-environmental damages of wastewater is began to appear, the strict formulation and implementation of China's environmental policies and the green upgrading of industrial structure are main driving forces, and it is little correlation with economic slowdown. This study offers the detailed list of China wastewater pollution and reveals the relationship between wastewater eco-environmental damages and economic development, and shows the experience and achievements of the Chinese government in the treatment of wastewater pollution, which provides a useful reference for the treatment of wastewater pollution in the world.

Emergy-based ecological efficiency evaluation and optimization method for logistics park.

With the rapid development of logistics park, how to evaluate and optimize the ecological efficiency of logistics park to achieve its sustainable development has become a concern of academia. In order to achieve this goal, this paper puts forward a method based on emergy, which processes the data in a unified dimension. By constructing the ecological efficiency evaluation model of logistics park, it quantitatively evaluates the ecological efficiency of logistics park, and analyzes the correlation between various factors and ecological efficiency. The application results of H logistics park show that fuel oil, information technology, net profit, and waste gas are closely related to the ecological efficiency of logistics park, and the correlation coefficients are 0.8248, -0.6949, 0.8544, and 0.7661, respectively. On this basis, the paper puts forward some suggestions to improve the ecological efficiency of the logistics park. This paper provides theoretical and methodological support for the evaluation and optimization of the ecological efficiency of the logistics park.

Circular RNA, microRNA and Protein Profiles of the Longissimus Dorsi of Germany ZIKA and Sichuan White Rabbits.

Due to the dietetic properties and remarkable nutritive value of rabbit meat, its industry is increasing rapidly. However, the association between circular RNAs, microRNAs, and proteins and muscle fiber type, and meat quality of rabbit is still unknown. Here, using deep sequencing and iTRAQ proteomics technologies we first identified 3159 circRNAs, 356 miRNAs, and 755 proteins in the longissimus dorsi tissues from Sichuan white (SCWrabs) and Germany great line ZIKA rabbits (ZIKArabs). Next, we identified 267 circRNAs, 3 miRNAs, and 29 proteins differentially expressed in the muscle tissues of SCWrabs and ZIKArabs. Interaction network analysis revealed some key regulation relationships between noncoding RNAs and proteins that might be associated with the muscle fiber type and meat quality of rabbit. Further, miRNA isoforms and gene variants identified in SCWrabs and ZIKArabs revealed some pathways and biological processes related to the muscle development. This is the first study of noncoding RNA and protein profiles for the two rabbit breeds. It provides a valuable resource for future studies in rabbits and will improve our understanding of the molecular regulation mechanisms in the muscle development of livestock. More importantly, the output of our study will benefit the researchers and producers in the rabbit breeding program.

Modeling analysis and lightweight design for an axle hub considering stress and fatigue life.

The lightweight of axle hub has been recognized as a typical representative of reducing the quality of vehicles for energy saving and emission reduction. Therefore, a modeling analysis and lightweight design based on ANSYS for axle hub is proposed. Firstly, design dimensions and structural parameters of axle hub are modeled. The hub model is imported into workbench software to simulate the static analysis. The stress and deformation of the axle hub are obtained by mesh element division, boundary condition constraints and loading conditions, and the modal and fatigue strength of the hub are simulated to obtain the modal natural frequency and life data. Then, from the point of view of reducing the quality and safety of the hub, the structure of the hub is changed, the model is compared again, and the lightweight design scheme can be obtained. The results show that the weight of a hub decreases by 5.537% after lightening. This method can improve the structure, save materials, reduce production costs, and shorten the design cycle. This lightweight design method has important reference and practical significance for the lightweight design of axle wheels and similar products.

Whole transcriptome sequencing reveals that non-coding RNAs are related to embryo morphogenesis and development in rabbits.

The roles of long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) in embryonic development remain unclear. We performed a comprehensive analysis of lncRNA and circRNA profiles in rabbit embryos at different stages by whole transcriptome sequencing. We identified 719 lncRNAs and 744 circRNAs that were differentially expressed between stages S1, S2 and S3. A total of 241 differentially expressed lncRNAs and 166 differentially expressed circRNAs were significantly involved in embryonic morphogenesis and development. An RNA network was established and of the embryonic development-associated RNAs, the lncRNAs TCONS_00009253 and TCONS_00010436 were persistently downregulated, while circRNA_07129, circRNA_15209, and circRNA_12526 were persistently upregulated, and their co-expressed mRNAs TBX1, WNT3 and FGFR2 were persistently downregulated during embryonic development. These candidate RNAs were mainly involved in the Wnt, PI3K-Akt, and calcium signaling pathways. This study reports candidate lncRNAs and circRNAs that may be indispensable for the morphogenesis and development of rabbit embryos.

The association of five preoperative serum tumor markers and pathological features in patients with breast cancer.

BACKGROUND: The utility of frequently used serum tumor markers in breast cancer remains controversial. The study aimed to investigate the role of preoperative carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), cancer antigen 153 (CA153), cancer antigen 724 (CA724), and ferritin (FER) in the management of breast cancer and their relationships with pathological features. METHODS: A total of 804 patients with breast mass who underwent breast surgery and 305 healthy volunteers were enrolled. Preoperative serum levels of CEA, CA125, CA153, CA724, and FER were measured. And the pathological features of all the patients were recorded. The association of preoperative serum tumor markers and pathological features was analyzed. RESULTS: Among the 804 patients, 355 were identified as malignant cases and 449 as benign cases. CEA, CA153, and FER of patients with breast cancer were higher than those of healthy volunteer group and patients with benign breast diseases. The area under curve (AUC) of CEA, CA153, and FER for distinguishing patients with breast cancer and subjects with non-breast cancer was 0.688 (95% CI: 0.656-0.721), 0.609 (95% CI: 0.574-0.645), and 0.623 (95% CI: 0.586-0.660), respectively. CA153 correlated with tumor size, node status, and TNM stage, whereas CA125 with node status. No statistic differences of the five markers were observed among the four molecular subtypes. CONCLUSION: Preoperative levels of CEA, CA153, and FER exhibit low diagnostic accuracy for breast cancer (stage I-III). CA153 correlates with tumor burden, suggesting its prognostic value. The five serum markers do not correlate with molecular subtypes.

[Meta-analysis of the diagnostic efficacy of heparin binding protein in adult sepsis].

OBJECTIVE: To evaluate the accuracy of heparin binding protein (HBP) in the diagnosis of adult sepsis by meta-analysis. METHODS: The retrospective, randomized controlled and prospective researches on the diagnosis of adult sepsis using HBP were reviewed by searching VIP network, China National Knowledge Infrastructure (CNKI), Wanfang database, PubMed, Embase and Web of Science from foundation to August 2018. The researches were selected according to inclusion and exclusion criteria, and QUADAS was used to evaluate the quality of eligible studies. Metadisc 14.0 was used to analyze the threshold effect, pool the estimation and do Meta regression analysis. Publication bias was assessed using Stata 12.0 with Deeks funnel plot. RESULTS: A total of 728 related literatures were searched and 14 studies were enrolled in this study with a total of 2 023 subjects, with 1 120 in sepsis group and 903 in non-sepsis control group (795 patients with non-sepsis and 108 healthy volunteers). The total score of literature quality was 14-23, indicating that the overall quality was good. Meta-analysis showed that Spearman correlation coefficient between sensitivity logorithm and 1-specificity logorithm of 14 groups of data was 0.106 (P = 0.719), indicating no threshold effect. The pooled sensitivity was 0.74 [95% confidence interval (95%CI) was 0.72-0.77], the pooled specificity was 0.73 (95%CI was 0.70-0.76), the diagnostic odds ratio (DOR) was 14.15 (95%CI was 7.77-25.78), and the area under summary receiver operating characteristic curve (AUC) was 0.865. Deeks funnel plot was asymmetrical on the left and right (P = 0.60), indicating that there was no publication bias of the eligible studies. CONCLUSIONS: HBP has good accuracy for the diagnosis of adult sepsis and it can be used as an auxiliary index for adult sepsis diagnosis.

Distribution of living coccolithophores in eastern Indian Ocean during spring intermonsoon.

We studied the biodiversity of autotrophic calcareous coccolithophore assemblages at 30 locations in the Eastern Equatorial Indian Ocean (EEIO) (80°-94°E, 6°N-5°S) and evaluated the importance of regional hydrology. We documented 26 species based on the identification of coccospheres and coccoliths, respectively. The coccolithophore community was dominated by Gephyrocapsa oceanica, Emiliania huxleyi, Florisphaera profunda, Umbilicosphaera sibogae, and Helicosphaera carteri. The abundance of coccoliths and coccospheres ranged from 0.2 × 103 to 160 × 103 coccoliths l-1 and 0.2 × 103 to 68 × 103 cells l-1, averaged 23 × 103 coccoliths l-1 and 9.4 × 103 cells l-1, respectively. Biogenic PIC, POC, and rain ratio mean values were 0.50 µgC l-1, 1.047 µgC l-1, and 0.10 respectively. High abundances of both coccoliths and coccospheres in the surface ocean layer occurred on the north of the equator. Vertically, the great majority of coccoliths and coccospheres were concentrated in water taken from depths of <75 m. The ratios between the number of coccospheres and free coccoliths indicated that coccoliths experience different levels of dissolution when transported to deep water. Abundant coccolithophores mainly occurred at the west of 90°E, which is in accordance with the presence of Wyrtki jets. Patterns of coccolithosphores and of coccoliths have been reflected in hydrological processes.

Identification of Long Non-Coding RNAs Related to Skeletal Muscle Development in Two Rabbit Breeds with Different Growth Rate.

Skeletal muscle development plays an important role in muscle quality and yield, which decides the economic value of livestock. Long non-coding RNAs (lncRNAs) have been reported to be associated with skeletal muscle development. However, little is revealed about the function of lncRNAs in rabbits' muscle development. LncRNAs and mRNAs in two rabbit breeds (ZIKA rabbits (ZKR) and Qixin rabbits (QXR)) with different growth rates at three developmental stages (0 day, 35 days, and 84 days after birth) were researched by transcriptome sequencing. Differentially expressed lncRNAs and mRNAs were identified for two rabbit breeds at the same stages by DESeq package. Co-expression correlation analysis of differentially expressed lncRNAs and mRNAs were performed to construct lncRNA⁻mRNA pairs. To explore the function of lncRNAs, Gene Ontology (GO) analysis of co-expression mRNAs in lncRNA⁻mRNA pairs were performed. In three comparisons, there were 128, 109, and 115 differentially expressed lncRNAs, respectively. LncRNAs TCONS_00013557 and XR_518424.2 differentially expressed in the two rabbit breeds might play important roles in skeletal muscle development, for their co-expressed mRNAs were significantly enriched in skeletal muscle development related GO terms. This study provides potentially functional lncRNAs in skeletal muscle development of two rabbit breeds and might be beneficial to the production of rabbits.

Dysifragilone A inhibits LPS­induced RAW264.7 macrophage activation by blocking the p38 MAPK signaling pathway.

Dysifragilone A, a sesquiterpene aminoquinone based on a rearranged avarone skeleton, has been previously isolated and identified from the South China Sea sponge Dysidea fragilis. In the present study, anti­inflammatory activity and the underlying molecular mechanism of dysifragilone A were studied using the classical inflammation model of lipopolysaccharide (LPS)­activated RAW264.7 macrophage cells and an MTT assay, Griess method, ELISA and western blotting were used. The results revealed that dysifragilone A significantly reduced the release of inflammatory mediators and inflammatory cytokines in activated RAW264.7 cells, including nitric oxide (NO), prostaglandin E2,(PGE2) and interleukin­6 (IL­6). The protein expression levels of inducible nitric oxide synthase (iNOS), cyclooxygenase­2 (COX­2), and the enzymatic activity of iNOS and COX­2 were also inhibited by dysifragilone A in a dose dependent manner. Further mechanistic investigations suggested that the anti­inflammatory activity of dysifragilone A results from the suppression of p38 mitogen­activated protein kinase (MAPK) activation in LPS­activated macrophages; however, this was not associated with inhibition of the extracellular signal­regulated kinase (ERK) or c­Jun N­terminal kinase (JNK) signaling pathways. Therefore, dysifragilone A and similar compounds may be anti­inflammatories that have potential to be used in the clinic.