Search

Predicting energy consumption in large exposition centers presents a significant challenge, primarily due to the limited datasets and fluctuating electricity usage patterns. This study introduces a cutting-edge algorithm, the contrastive transformer network (CTN), to address these issues. By leveraging self-supervised learning, the CTN employs contrastive learning techniques across both temporal and contextual dimensions. Its transformer-based architecture, tailored for efficient feature extraction, allows the CTN to excel in predicting energy consumption in expansive structures, especially when data samples are scarce. Rigorous experiments on a proprietary dataset underscore the potency of the CTN in this domain. [ABSTRACT FROM AUTHOR]

Novel TiO2 nanoparticles-coated CNTs (TiO2@CNTs) fabricated by the alcohol-thermal method were used as the reinforcement to prepare aluminum matrix composites through high-intensity ultrasonic-assisted casting, followed by heat treatment. The results of optical microscope showed that the optimum heat treatment process was solution treatment (495 °C, 2 h) + aging treatment (180 °C, 12 h). Under this condition, the Al2Cu and Al2CuMg phases were uniformly precipitated in the composites, and most of them were in a discrete state. TEM results revealed that TiO2 nanoparticles dispersed on the surface of CNTs played the role of an interlayer structure between CNTs and matrix, locking the CNTs and improving the CNTs–Al interfacial bonding. The ultimate tensile strength (UTS) and yield strength (YS) of 1.0 wt%TiO2@CNTs/2024 composite after T6 heat treatment reach 324 MPa and 219 MPa, respectively, which exhibited enhanced UTS and YS than the monolithic 2024 alloy. This was attributed to the synergistic strengthening of multi-mechanisms, such as grain refinement strengthening, load transfer strengthening, dislocation strengthening and, especially, Orowan strengthening. [ABSTRACT FROM AUTHOR]

• A novel gram-scale (around 1.66 g) diatomic sites catalyst CN-NiZn is synthesized. • The NiN 3 /ZnN 3 sites of CN-NiZn own synergistic effect for converting CO 2 to CO. • CN-NiZn shows over 92 % FE CO from −0.57 to −1.07 V, especially 97.5 % FE CO at −0.77 V. • CN-NiZn can maintain FE CO of exceeding 90 % at −0.77 V during 30 h of electrolysis. Diatomic catalysts inherit the advantages of single atom catalysts and use the adjacent metal-N sites for functional complementary and synergistic effects in electrochemical CO 2 reduction (ECR). However, preparation of diatomic catalysts with high yield, Faradaic efficiency and stability together with low overpotential still remains challenging. In this work, we develop a nitrogen-doped carbon supported Ni-Zn diatomic catalyst, whose CO Faradaic efficiency of is higher than 92.0 % in the wide potential range of −0.57 ∼ −1.07 V vs RHE, and the maximum CO Faradaic efficiency is 97.5 % at −0.77 V vs RHE. And also, CN-NiZn performs an extraordinary stability for 30 h in the long-time durability test. More importantly, large-quantities (around 1.66 g) of Ni-Zn diatomic catalysts with remarkable catalytic performance can be prepared by this method. Synchrotron radiation X-ray absorption spectroscopy was tested to reflect the coordination environment and valence states around Ni and Zn atoms. Theoretical calculations further reveal that the synergistic effect between Ni and Zn binary metal sites largely reduces the energy barrier of the reaction to produce the intermediate *COOH, thus effectively increasing the selectivity of ECR. This work indicates that the introduction of another coordination metal can significantly affect the electronic structure of monatomic catalysts, thus improving the electrocatalytic activity and selectivity of ECR. [Display omitted] [ABSTRACT FROM AUTHOR]

Hyperspectral classification is a fundamental problem for applying hyperspectral technology, and unsupervised learning is a promising direction to address the issue. Unsupervised feature learning algorithm extracts representative features, which help efficiently classify the hyperspectral pixels. This paper combines the popular contrastive learning method (prototypical contrastive learning) and the classic representation learning method (autoencoder) to design an unsupervised feature learning network for hyperspectral classification. First, two different encoders are used to extract different features as augmentation function in a contrastive network (ContrastNet). Second, the prototypical contrastive learning method is adopted to train a contrastive network. Third, features extracted by the contrastive network are used for classification. Experiments have proved that our two proposed autoencoder networks show good feature learning capabilities by themselves and the designed contrastive learning network can further learn better representative features from the two modules. The three modules compose an efficient framework for unsupervised feature learning. Our method also performs reasonably fast in the testing phase, which implies that it is applicable in practice under specific conditions. [ABSTRACT FROM AUTHOR]

Hyperspectral classification is a fundamental problem for applying hyperspectral technology, and unsupervised learning is a promising direction to address the issue. Unsupervised feature learning algorithm extracts representative features, which help efficiently classify the hyperspectral pixels. This paper combines the popular contrastive learning method (prototypical contrastive learning) and the classic representation learning method (autoencoder) to design an unsupervised feature learning network for hyperspectral classification. First, two different encoders are used to extract different features as augmentation function in a contrastive network (ContrastNet). Second, the prototypical contrastive learning method is adopted to train a contrastive network. Third, features extracted by the contrastive network are used for classification. Experiments have proved that our two proposed autoencoder networks show good feature learning capabilities by themselves and the designed contrastive learning network can further learn better representative features from the two modules. The three modules compose an efficient framework for unsupervised feature learning. Our method also performs reasonably fast in the testing phase, which implies that it is applicable in practice under specific conditions. [ABSTRACT FROM AUTHOR]

Designing and synthesising electrocatalysts with low overpotential, high activity, selectivity, and stability for the CO 2 reduction reaction (CO 2 RR) is crucial for addressing environmental challenges and realising the artificial carbon cycle. In this study, we successfully synthesised a nitrogen-doped carbon-supported diatomic electrocatalyst comprising atomically dispersed CuN 4 and NiN 4 bimetallic centers. This was confirmed through extensive characterisation using high-angle annular dark-field scanning transmission electron microscopy and X-ray absorption spectroscopy techniques. The as-synthesised CBN-CuNi electrocatalyst exhibited exceptional selectivity and stability in CO 2 RR. Over a wide potential range from − 0.60 to − 1.10 V vs RHE, CBN-CuNi maintained over 90% Faraday efficiency for CO (FE CO) production. Notably, at − 0.9 V vs RHE, it achieved a remarkable selectivity with a maximum FE CO of 97.9%, surpassing single metal catalysts, including CBN-Ni and CBN-Cu. Furthermore, CBN-CuNi demonstrated outstanding stability, sustaining over 90% FE CO production for 40 h of continuous electrolysis, surpassing many existing electrocatalysts. These findings highlight the potential of the as-synthesised bimetallic electrocatalyst CBN-CuNi in the electrochemical reduction of CO 2 to CO, contributing to advancing the artificial carbon cycle and addressing environmental concerns. [Display omitted] • A novel nitrogen-doped carbon-supported electrocatalyst CBN-CuNi is synthesized. • The CuN 4 /NiN 4 coordination environment of CBN-CuNi promotes the convert CO 2 into CO. • CBN-CuNi shows over 90% FE CO from − 0.6 to − 1.1 V, especially 97.9% FE CO at − 0.9 V. • CBN-CuNi can maintain FE CO of exceeding 90% at − 0.8 V during 40 h of electrolysis. [ABSTRACT FROM AUTHOR]

Gas emission is a major security risk in coal mining. Seal coating is an effective method for preventing gas from escaping, but the stability of inorganic particles in the coating has great influence on the sealing performance. This research was designed to study the effect of SHMP on the stability of a gas-sealing coating filler based on UFA. The effect of SHMP on powder dispersion behaviors was systematically investigated using a zeta potential tester, particle size analyzer, FT-IR, and SEM- EDS. To explore the dispersion mechanism of SHMP on typical powder materials (such as fly ash, carbon black, and graphite), the interaction energy among particles was calculated according to the classical and extended DLVO theory. The results indicate that the surface hydrophobic effects of graphite and carbon black were the main contributing factors to agglomeration. Further, the dispersant SHMP increases the interparticle electrostatic repulsions and steric hindrance, preventing particle agglomeration and ensuring the stability of fly ash-based filler in gas-sealing coatings. The results of pilot spraying test in a coal mine show that the added dispersant improved the gas-sealing efficiency of the coating and helped in its application in a coal mine. Image 1 • SHMP increases the inter particle electrostatic repulsions and steric hindrance. • Fly ash can be used as a kind of good filler in coating products. • The repulsive energy among particles agreed with extended DLVO theory. • The pilot test verified the gas sealing efficiency of the coating with SHMP. [ABSTRACT FROM AUTHOR]

Botulinum toxin type A (BoNT-A) has been recommended in various neurological disorders as a useful tool for alleviating dystonia. In Wilson disease (WD) patients with dystonia, BoNT-A injection can be used as a treatment modality when conventional treatment is ineffective for alleviating symptoms. The purpose of this study was to thoroughly evaluate the efficacy of BoNT-A injection in treating WD complicated by lower extremity dystonia. The efficacy of these injections was assessed by clinical scales, surface electromyography (EMG), and gait analysis. A comparative analysis of all gait parameters, EMG parameters, and clinical scales revealed a significant increase in velocity, decrease in integrated EMG (iEMG), and improvement in modified Ashworth scale (MAS), Burke Fahn Marsden (BFM), and activities of daily living (ADL) scores (all P < 0.05). Overall, our findings indicated that BoNT-A injection led to marked relief of symptoms in patients with WD with lower extremity dystonia. [Display omitted] • Single-blind, pre-and post-intervention study were initially performed in Wilson disease patients with lower limb dystonia. • Botulinum toxin type A injection improves the muscle tone, as evident by the decrease in integrated electromyogram. • Botulinum toxin type A injection improves walking function, as evident by the increase in velocity. • Botulinum toxin type A injection alleviates the symptoms of lower limb dystonia in Wilson disease patients. [ABSTRACT FROM AUTHOR]

Luteoloside is a member of the flavonoids family that exhibits several bioactivities including anti-microbial and anti-cancer activities. However, the antiviral activity of luteoloside against enterovirus 71 (EV71) and the potential mechanism(s) responsible for this effect remain unknown. In this study, the antiviral potency of luteoloside against EV71 and its inhibitory effects on 3C protease activity were evaluated. First, we investigated the cytotoxicity of luteoloside against rhabdomyosarcoma (RD) cells, which was the cell line selected for an in vitro infection model. In a subsequent antiviral assay, the cytopathic effect of EV71 was significantly and dose-dependently relieved by the administration of luteoloside (EC50 = 0.43 mM, selection index = 5.3). Using a plaque reduction assay, we administered luteoloside at various time points and found that the compound reduced EV71 viability in RD cells rather than increasing defensive mobilization or viral absorption. Moreover, biochemical studies focused on VP1 (a key structural protein of EV71) mRNA transcript and protein levels also revealed the inhibitory effects of luteoloside on the EV71 viral yield. Finally, we performed inhibition assays using luteoloside to evaluate its effect on recombinant 3C protease activity. Our results demonstrated that luteoloside blocked 3C protease enzymatic activity in a dose-dependent manner (IC50 = 0.36 mM) that was similar to the effect of rutin, which is a well-known C3 protease inhibitor. Collectively, the results from this study indicate that luteoloside can block 3C protease activity and subsequently inhibit EV71 production in vitro. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are widely recognized as low-carbon transportation that adopts green and clean technology with contributing to mitigating global climate change. However, it appears that the practice in using EVs has not gained widespread popularity despite the promotion of various incentives with the presence of various restricting factors and challenges. In conducting this study in the context of China, we hypothesize that restricting factors have varying impacts on promoting EVs in China, where the adoption of EVs is of great potential. This paper identifies these restricting factors by applying AHP-FCE integrated approach, and these factors are classified into five dimensions, namely, technical, infrastructural, economic, governance and social. The results indicate that the top five restricting factors are security issues, limited driving range, long charging time, improper distribution of charging stations and lack of sharing between charging piles respectively. Our research contributes to a better understanding of EV restricting factors and their significance, which offers the assistance in the formulation of policies and decisions in order to promote effectively EVs in China. • The promotion of EVs is of great potential in China for mitigating global climate change. • Explore the RFPEVs in China using AHP-FCE integrated approach. • The RFPEVs in China can be classified into five dimensions, namely, technical, infrastructural, economic, governance and social. • The technical and infrastructural related are the most important constraints. • The main three important restricting factors are security issues, limited driving range, long charging time. [ABSTRACT FROM AUTHOR]

A set of crosslinked quaternized polybenzimidazole (cQAPBI-nC) membranes with varying carbon chain lengths of crosslinking agents are designed and prepared through grafting and crosslinking reactions for their applications in electrocatalytic CO 2 reduction reaction (CO 2 RR). The cQAPBI-6C membrane stands out among all the cQAPBI-nC membranes due to its ingenious construction of a hydrophilic/hydrophobic micro-phase separation structure. As a result, this membrane exhibits exceptional OH− conductivity and selectivity of 79.40 mS cm−1 and 54.73%, respectively, surpassing those of the commercially available FAA-3-PK-130 membrane (OH− conductivity: 33.38 mS cm−1, selectivity: 39.00%). Moreover, the cQAPBI-6C membrane has excellent mechanical and alkaline stabilities. In the self-made membrane electrode assembly reactor, the cQAPBI-6C membrane demonstrates higher CO Faraday efficiency (FE) compared with FAA-3-PK-130 membrane at −100 ∼ −160 mA cm−2. Furthermore, the cQAPBI-6C membrane can operate continuously and stably for over 32 h at −150 mA cm−2, and the CO FE and voltage maintain at around 95% and −3.7 V. These findings provide strong evidence to support the practical significance of the proposed modification strategy in the development of polybenzimidazole-based anion exchange membranes for CO 2 RR applications. [Display omitted] • cQAPBI membranes were prepared via grafting and crosslinking strategies for CO 2 RR. • The obvious micro-phase separation structure is given to cQAPBI-6C membrane. • cQAPBI-6C membrane has outstanding OH−conductivity and selectivity. • cQAPBI-6C membrane shows excellent CO FE, current density and durability for CO 2 RR. [ABSTRACT FROM AUTHOR]

• Introducing the extended transient current region by adopting short-time overcurrent capacity of grid-side converter. • Current relaxation region (CRR) is proposed for description of transient current boundary and look-up table design. • A novel CRR-based LVRT strategy is proposed to alleviate active current reduction while maintaining the reactive current ability. This paper proposes a current relation region (CRR)-based low-voltage ride-through (LVRT) strategy for offshore wind turbines (OWTs). The proposed strategy seeks to minimize the detrimental shortfall of OWT's active current on the premise of maintaining the reactive support ability by considering short-time overcurrent capacity of grid-side converter (GSC) during low-voltage fault. Firstly, the extended transient current region (ETCR) is introduced to improve the transient current ability of OWTs with comparison to conventional transient current region (CTCR) based on rated current capacity of GSC. Combined with the introduced ETCR, grid code constraint and wind speed constraint are investigated for detailed description of OWT's transient current boundary of CRR. Furthermore, we design the CRR-based LVRT strategy with look-up tables to facilitate dispatching the transient current instructions to OWTs' controllers. Finally, extensive case studies based on PSCAD are performed and the results show that the proposed strategy can improve active current and reactive current simultaneously over the conventional strategy. In the scenario of the rated wind speed (11.4 m/s) and critical voltage (0.2 p.u.), this achievement can be clearly seen by the value improvement in the active current and reactive current by 0.328 p.u. and 0.05 p.u., respectively. [ABSTRACT FROM AUTHOR]

Lonicera japonica Thunb, rich in chlorogenic acid (CHA), is used for viral upper respiratory tract infection treatment caused by influenza virus, parainfluenza virus, and respiratory syncytial virus, ect in China. It was reported that CHA reduced serum hepatitis B virus level and death rate of influenza virus-infected mice. However, the underlying mechanisms of CHA against the influenza A virus have not been fully elucidated. Here, the antiviral effects and potential mechanisms of CHA against influenza A virus were investigated. CHA revealed inhibitory against A/PuertoRico/8/1934(H1N1) (EC50 = 44.87 μM), A/Beijing/32/92(H3N2) (EC50 = 62.33 μM), and oseltamivir-resistant strains. Time-course analysis showed CHA inhibited influenza virus during the late stage of infectious cycle. Indirect immunofluorescence assay indicated CHA down-regulated the NP protein expression. The inhibition of neuraminidase activity confirmed CHA blocked release of newly formed virus particles from infected cells. Intravenous injection of 100 mg/kg/d CHA possessed effective antiviral activity in mice, conferring 60% and 50% protection from death against H1N1 and H3N2, reducing virus titres and alleviating inflammation in the lungs effectively. These results demonstrate that CHA acts as a neuraminidase blocker to inhibit influenza A virus both in cellular and animal models. Thus, CHA has potential utility in the treatment of the influenza virus infection. [ABSTRACT FROM AUTHOR]

The noise corruption problem commonly exists in hyperspectral images (HSIs) and severely affects the accuracy of hyperspectral unmixing algorithms. The noise formulation existing in HSIs is relatively complex and would change in conjunction with different devices and imaging settings. For real applications, applying denoising approaches without accurate close-to-reality noise modeling before unmixing may not improve, but rather degrade the unmixing performance. This study proposes a robust hyperspectral unmixing method with practical learning-based hyperspectral image denoising. We formulated a close-to-reality noise model for hyperspectral data and provide a calibration approach for the noise parameters. On the basis of the calibrated noise model, synthetic data were generated and used for training a KST-based denoising network. The noisy hyperspectral data were firstly denoised by the trained denoising network and were then used to perform the unmixing process. A variety of unmixing algorithms can be integrated into our method to improve the accuracy of unmixing in noisy situations. In the experiments, several widely used unmixing algorithms were employed to verify the effect of the proposed method. The experimental results on both synthetic and real demonstrated that our proposed method can handle HSI data with various gain settings and helps to improve the unmixing performance effectively. [ABSTRACT FROM AUTHOR]

Neurodegenerative diseases, referring to as the progressive loss of structure and function of neurons, constitute one of the major challenges of modern medicine. Traditional Chinese herbs have been used as a major preventive and therapeutic strategy against disease for thousands years. The numerous species of medicinal herbs and Traditional Chinese Medicine (TCM) compound formulas in nervous system disease therapy make it a large chemical resource library for drug discovery. In this work, we collected 7362 kinds of herbs and 58,147 Traditional Chinese medicinal compounds (Tcmcs). The predicted active compounds in herbs have good oral bioavailability and central nervous system (CNS) permeability. The molecular docking and network analysis were employed to analyze the effects of herbs on neurodegenerative diseases. In order to evaluate the predicted efficacy of herbs, automated text mining was utilized to exhaustively search in PubMed by some related keywords. After that, receiver operator characteristic (ROC) curves was used to estimate the accuracy of predictions. Our study suggested that most herbs were distributed in family of Asteraceae, Fabaceae, Lamiaceae and Apocynaceae. The predictive model yielded good sensitivity and specificity with the AUC values above 0.800. At last, 504 kinds of herbs were obtained by using the optimal cutoff values in ROC curves. These 504 herbs would be the most potential herb resources for neurodegenerative diseases treatment. This study would give us an opportunity to use these herbs as a chemical resource library for drug discovery of anti-neurodegenerative disease. [ABSTRACT FROM AUTHOR]

Key message: By using pharmacological and molecular approaches, we discovered the involvement of HO-1 in NaHS-induced lateral root formation in tomato seedlings. Abstract: Heme oxygenase-1 (HO-1) and hydrogen sulfide (HS) regulate various responses to abiotic stress and root development, but their involvement in the simultaneous regulation of plant lateral root (LR) formation is poorly understood. In this report, we observed that the exogenously applied HS donor sodium hydrosulfide (NaHS) and the HO-1 inducer hemin induce LR formation in tomato seedlings by triggering intracellular signaling events involving the induction of tomato HO- 1 ( SlHO- 1), and the modulation of cell cycle regulatory genes, including the up-regulation of SlCDKA;1 and SlCYCA2;1, and simultaneous down-regulation of SlKRP2. The response of NaHS in the induction of LR formation was impaired by the potent inhibition of HO-1, which was further blocked when 50 % saturation of carbon monoxide (CO) aqueous solution, one of the catalytic by-products of HO-1, was added. Further molecular evidence revealed that the NaHS-modulated gene expression of cell cycle regulatory genes was sensitive to the inhibition of HO-1 and reversed by cotreatment with CO. The impairment of LR density and length as well as lateral root primordia number, the decreased tomato HO- 1 gene expression and HO activity caused by an HS scavenger hypotaurine were partially rescued by the addition of NaHS, hemin and CO (in particular). Together, these results revealed that at least in our experimental conditions, HO-1 might be involved in NaHS-induced tomato LR formation. Additionally, the use of NaHS and hemin compounds in crop root organogenesis should be explored. [ABSTRACT FROM AUTHOR]

Prompted by the prominent role of angiotensin converting enzyme (ACE) in hypertension, heart failures, myocardial infarction and diabetic nephropathy, we have attempted to discover novel ACE inhibitors through ligand-based virtual screening. Molecular docking method and rigorously validated model was utilized to search a natural compounds database. Finally, 36 compounds were randomly selected and subjected to in vitro ACE kinase inhibitory assay using fluorescence assays method. The results showed that three compounds (Licochalcone A, Echinatin and EGCG) have strong potential to be developed as a new class of ACE inhibitors. Further chemical modification via fragment modifications guided by structure and ligand-based computational methodologies can lead to discover better agents as potential clinical candidates. [ABSTRACT FROM AUTHOR]

Light intensity and nitrogen concentration of nutrient solution are considered crucial for the contents of vitamin C and nitrate in cultivated leaf vegetables. We here investigated the effects of various combinations of light intensity (60, 140 and 220 μmol m −2 s −1 ) and nitrogen concentration (7, 15 and 23 mmol L −1 ) of the solution on the growth, photosynthetic characteristics, vitamin C and nitrate content of lettuce. Our results demonstrate that the lettuce had the largest dry biomass at the high illumination of 220 μmol m −2 s −1 and low nitrogen of 7 mmol L −1 . The higher light and low nitrogen also contributed to the accumulation of vitamin C and decrease of nitrate in lettuce leaves. The effect of nitrogen supply on chlorophyll concentrations was more efficient under low light than high illumination. Our results reveal that there was an obvious interaction between light intensity and nitrogen available for the photosynthesis, yield and quality of lettuce. This study provides valuable insights into the combinational regulation of light intensity and nitrogen supply for improving growth and nutritional quality of vegetables grown in greenhouse and plant factory. [ABSTRACT FROM AUTHOR]

Reduning injection (RDNI) is a patented Traditional Chinese medicine that contains three Chinese herbal medicines, respectively are the dry aboveground part of Artemisia annua L. , the flower of Lonicera japonica Thunb. , and the fruit Gardenia jasminoides J.Ellis. RDNI has been recommended for treating Coronavirus Disease 2019 (COVID-19) in the "New Coronavirus Pneumonia Diagnosis and Treatment Plan". To elucidate and verify the underlying mechanisms of RDNI for the treatment of COVID-19. This study firstly performed anti-SARS-CoV-2 experiments in Vero E6 cells. Then, network pharmacology combined with molecular docking was adopted to explore the potential mechanisms of RDNI in the treatment for COVID-19. After that, western blot and a cytokine chip were used to validate the predictive results. We concluded that half toxic concentration of drug CC50 (dilution ratio) = 1:1280, CC50 = 2.031 mg crude drugs/mL (0.047 mg solid content/mL) and half effective concentration of drug (EC50) (diluted multiples) = 1:25140.3, EC50 = 103.420 μg crude drugs/mL (2.405 μg solid content/mL). We found that RDNI can mainly regulate targets like carbonic anhydrases (CAs), matrix metallopeptidases (MMPs) and pathways like PI3K/AKT, MAPK, Forkhead box O s and T cell receptor signaling pathways to reduce lung damage. We verified that RDNI could effectively inhibit the overexpression of MAPKs, PKC and p65 nuclear factor-κB. The injection could also affect cytokine levels, reduce inflammation and display antipyretic activity. RDNI can regulate ACE2, Mpro and PLP in COVID-19. The underlying mechanisms of RDNI in the treatment for COVID-19 may be related to the modulation of the cytokine levels and inflammation and its antipyretic activity by regulating the expression of MAPKs, PKC and p65 nuclear factor NF-κB. [Display omitted] [ABSTRACT FROM AUTHOR]

Seven undescribed labdane diterpenoids, japonicones A-G, were isolated from the aerial parts of Leonurus japonicus Houtt. Japonicones C-G contained two keto carbonyl groups in their structures attached to C-3 and C-7, which are rare for labdane diterpenoids. The structures and absolute configurations of japonicones A-G were established by means of spectroscopic analyses (HRESIMS, 1D and 2D NMR, and ECD). Their anti-inflammatory activities were evaluated by measuring their inhibitory effects on PGE 2 production in LPS-stimulated RAW264.7 macrophages. Japonicones A-D and G showed inhibition of PGE 2 production with IC 50 values in the range of 8.62–30.71 μ M (the positive control paracetamol showed an IC 50 = 5.79 μ M). Image 1 • Seven undescribed labdane diterpenoids were isolated from the aerial parts of Leonurus japonicus Houtt. • Their structures and absolute configurations were established by means of spectroscopic analyses. • Compounds 1 − 4 , and 7 showed inhibition of PGE 2 production with IC 50 values in the range of 8.62−30.71 μ M. [ABSTRACT FROM AUTHOR]