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Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating, and enabling our understanding of natural phenomena at a wide range of spatial and temporal scales, giving rise to a new area of research known as AI for science (AI4Science). Being an emerging research paradigm, AI4Science is unique in that it is an enormous and highly interdisciplinary area. Thus, a unified and technical treatment of this field is needed yet challenging. This paper aims to provide a technically thorough account of a subarea of AI4Science; namely, AI for quantum, atomistic, and continuum systems. These areas aim at understanding the physical world from the subatomic (wavefunctions and electron density), atomic (molecules, proteins, materials, and interactions), to macro (fluids, climate, and subsurface) scales and form an important subarea of AI4Science. A unique advantage of focusing on these areas is that they largely share a common set of challenges, thereby allowing a unified and foundational treatment. A key common challenge is how to capture physics first principles, especially symmetries, in natural systems by deep learning methods. We provide an in-depth yet intuitive account of techniques to achieve equivariance to symmetry transformations. We also discuss other common technical challenges, including explainability, out-of-distribution generalization, knowledge transfer with foundation and large language models, and uncertainty quantification. To facilitate learning and education, we provide categorized lists of resources that we found to be useful. We strive to be thorough and unified and hope this initial effort may trigger more community interests and efforts to further advance AI4Science.

Geometric deep learning enables the encoding of physical symmetries in modeling 3D objects. Despite rapid progress in encoding 3D symmetries into Graph Neural Networks (GNNs), a comprehensive evaluation of the expressiveness of these networks through a local-to-global analysis lacks today. In this paper, we propose a local hierarchy of 3D isomorphism to evaluate the expressive power of equivariant GNNs and investigate the process of representing global geometric information from local patches. Our work leads to two crucial modules for designing expressive and efficient geometric GNNs; namely local substructure encoding (LSE) and frame transition encoding (FTE). To demonstrate the applicability of our theory, we propose LEFTNet which effectively implements these modules and achieves state-of-the-art performance on both scalar-valued and vector-valued molecular property prediction tasks. We further point out the design space for future developments of equivariant graph neural networks. Our codes are available at \url{https://github.com/yuanqidu/LeftNet}.

Many real-world data can be modeled as 3D graphs, but learning representations that incorporates 3D information completely and efficiently is challenging. Existing methods either use partial 3D information, or suffer from excessive computational cost. To incorporate 3D information completely and efficiently, we propose a novel message passing scheme that operates within 1-hop neighborhood. Our method guarantees full completeness of 3D information on 3D graphs by achieving global and local completeness. Notably, we propose the important rotation angles to fulfill global completeness. Additionally, we show that our method is orders of magnitude faster than prior methods. We provide rigorous proof of completeness and analysis of time complexity for our methods. As molecules are in essence quantum systems, we build the \underline{com}plete and \underline{e}fficient graph neural network (ComENet) by combing quantum inspired basis functions and the proposed message passing scheme. Experimental results demonstrate the capability and efficiency of ComENet, especially on real-world datasets that are large in both numbers and sizes of graphs. Our code is publicly available as part of the DIG library (\url{https://github.com/divelab/DIG})., The paper has been accepted by NeurIPS 2022. You can also cite the conference version

Training of graph neural networks (GNNs) for large-scale node classification is challenging. A key difficulty lies in obtaining accurate hidden node representations while avoiding the neighborhood explosion problem. Here, we propose a new technique, named feature momentum (FM), that uses a momentum step to incorporate historical embeddings when updating feature representations. We develop two specific algorithms, known as GraphFM-IB and GraphFM-OB, that consider in-batch and out-of-batch data, respectively. GraphFM-IB applies FM to in-batch sampled data, while GraphFM-OB applies FM to out-of-batch data that are 1-hop neighborhood of in-batch data. We provide a convergence analysis for GraphFM-IB and some theoretical insight for GraphFM-OB. Empirically, we observe that GraphFM-IB can effectively alleviate the neighborhood explosion problem of existing methods. In addition, GraphFM-OB achieves promising performance on multiple large-scale graph datasets., ICML 2022

Context Current medicine for Alzheimer's disease (AD) cannot effectively reverse or block nerve injury. Traditional Chinese Medicine practice and research imply Aconiti lateralis Radix Praeparata (Fuzi) may meet this goal. Objective Analysing the anti-AD effect of Fuzi and its potential molecular mechanism. Materials and methods AD model cells were treated with Fuzi in 0-300 mg/mL for 24 h in 37 °C. The cell viability (CV) and length of cell projections (LCP) for each group were observed, analysed, and standardised using control as a baseline (CVs and LCPs). The Fuzi and AD relevant genes were identified basing on databases, and the molecular mechanism of Fuzi anti-AD was predicted by network analysis. Results Experiment results showed that Fuzi in 0.4 mg/mL boosted LCP (LCPs = 1.2533, p ≤ 0.05), and in 1.6-100 mg/mL increased CV (CVs from 1.1673 to 1.3321, p ≤ 0.05). Bioinformatics analysis found 17 Fuzi target genes (relevant scores ≥ 20), showing strong AD relevant signals (RMS_p ≤ 0.05, related scores ≥ 5), enriched in the pathways regulating axon growth, synaptic plasticity, cell survival, proliferation, apoptosis, and death (p ≤ 0.05). Especially, GRIN1 and MAPK1 interacted with APP protein and located in the key point of the "Alzheimer's disease" pathway. Discussion and conclusions These results suggest that Fuzi may have therapeutic and prevention potential in AD, and GRIN1 and MAPK1 may be the core of the pathways of the Fuzi anti-AD process. Fuzi should be studied more extensively, especially for the prevention of AD.

The SARS-CoV-2 pandemic remains an ongoing threat to global health with emerging variants, especially the Omicron variant and its sub-lineages. Although large-scale vaccination worldwide has delivered outstanding achievements for COVID-19 prevention, a declining effectiveness to a different extent in emerging SARS-CoV-2 variants was observed in the vaccinated population. Vaccines eliciting broader spectrum neutralizing antibodies and cellular immune responses are urgently needed and important. To achieve this goal, rational vaccine design, including antigen modeling, screening and combination, vaccine pipelines, and delivery, are keys to developing a next-generation COVID-19 vaccine. In this study, we designed several DNA constructs based on codon-optimized spike coding regions of several SARS-CoV-2 variants and analyzed their cross-reactive antibodies, including neutralizing antibodies, and cellular immune responses against several VOCs in C57BL/6 mice. The results revealed that different SARS-CoV-2 VOCs induced different cross-reactivity; pBeta, a DNA vaccine encoding the spike protein of the Beta variant, elicited broader cross-reactive neutralizing antibodies against other variants including the Omicron variants BA.1 and BA.4/5. This result demonstrates that the spike antigen from the Beta variant potentially serves as one of the antigens for multivalent vaccine design and development against variants of SARS-CoV-2.

This study used response surface methodology to determine the optimal conditions for extraction of polysaccharides from Pyracantha. fortuneana (PSPF), and studied the mechanism of PSPF-inducing apoptosis in human ovarian carcinoma Skov3 cells. Response surface methodology (RSM) were adopted to extract PSPF. The maximum value of polysaccharide yield was obtained under these optimal conditions. PSPF had good potential as an antioxidant. Exposure of cells to PSPF resulted in cytotoxicity through the induction of apoptosis, and the reactive oxygen species were increased, mitochondrial membrane potential decreased, DNA damage (detected as γ- H2AX and RAD51 foci) was observed in Skov3 cells. In addition, PSPF could induce apoptosis of cancer cells. Therefore, PSPF should be explored as novel potential antioxidants and an anti-tumor drug in a clinical setting.

Ethylene response factor (ERF) genes have been characterized in numerous plants, where they are associated with responses to biotic and abiotic stress. Modified atmosphere packaging (MAP) is an effective treatment to prevent lotus root browning. However, the possible relationship between ERF transcription factors and lotus root browning under MAP remains unexplored. In this study, the effects of phenol, phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO), and peroxidase (POD) enzyme activities; and PPO, PAL, POD, and ERF gene expression on fresh-cut lotus root browning were studied with MAP. The expression pattern of ERF2/5 correlated highly with the degree of browning. It is suggested that NnERF2/5 can be used as an important candidate gene for the regulation of fresh-cut lotus root browning under MAP, and the correlation of each gene should be studied further.

BackgroundThis study aimed to observe the application and evaluate the feasibility and safety of indocyanine green (ICG) fluorescence technology in laparoscopic radical gastrectomy (LRG).MethodsPatients who underwent LRG & D2 lymphadenectomy at Qilu Hospital of Shandong University were included between January 2018 and August 2019. According to whether endoscopic injection of ICG was performed, patients were assigned to the ICG group (n=107) and the control group (n=88). The clinicopathologic features, retrieved lymph nodes, postoperative recovery, and follow-up data were compared between the two groups.ResultsBaseline characteristics are comparable. The ICG group had a significantly larger number of lymph nodes retrieved (49.55 ± 12.72 vs. 44.44 ± 10.20, P0.05) or DFS (86.0% vs. 80.7%, P>0.05).ConclusionsICG fluorescence technology in laparoscopic radical gastrectomy has advantages in LN dissection, operation time, and intraoperative blood loss. The 2-year OS and 2-year DFS rates between the two groups were comparable. In conclusion, ICG fluorescence technology is feasible and safe.

Out-of-distribution (OOD) learning deals with scenarios in which training and test data follow different distributions. Although general OOD problems have been intensively studied in machine learning, graph OOD is only an emerging area of research. Currently, there lacks a systematic benchmark tailored to graph OOD method evaluation. In this work, we aim at developing an OOD benchmark, known as GOOD, for graphs specifically. We explicitly make distinctions between covariate and concept shifts and design data splits that accurately reflect different shifts. We consider both graph and node prediction tasks as there are key differences in designing shifts. Overall, GOOD contains 11 datasets with 17 domain selections. When combined with covariate, concept, and no shifts, we obtain 51 different splits. We provide performance results on 10 commonly used baseline methods with 10 random runs. This results in 510 dataset-model combinations in total. Our results show significant performance gaps between in-distribution and OOD settings. Our results also shed light on different performance trends between covariate and concept shifts by different methods. Our GOOD benchmark is a growing project and expects to expand in both quantity and variety of resources as the area develops. The GOOD benchmark can be accessed via https://github.com/divelab/GOOD/.

Antibody-mediated cancer immunotherapy targets inhibitory surface molecules, such as PD1, PD-L1, and CTLA-4, aiming to re-invigorate dysfunctional T cells. We purified and characterized tumor-infiltrating lymphocytes (TILs) and their patient-matched non-tumor counterparts from treatment-naive NSCLC patient biopsies to evaluate the effect of PD1 expression on the functional and molecular profiles of tumor-resident T cells. We show that PD1+ CD8+ TILs have elevated expression of the transcriptional regulator ID3 and that the cytotoxic potential of CD8 T cells can be improved by knocking down ID3, defining it as a potential regulator of T cell effector function. PD1+ CD4 + memory TILs display transcriptional patterns consistent with both helper and regulator function, but can robustly facilitate B cell activation and expansion. Furthermore, we show that expanding ex vivo-prepared TILs in vitro broadly preserves their functionality with respect to tumor cell killing, B cell help, and TCR repertoire. Although purified PD1+ CD8+ TILs generally maintain an exhausted phenotype upon expansion in vitro, transcriptional analysis reveals a downregulation of markers of T-cell dysfunction, including the co-inhibitory molecules PD1 and CTLA-4 and transcription factors ID3, TOX and TOX2, while genes involved in cell cycle and DNA repair are upregulated. We find reduced expression of WNT signaling components to be a hallmark of PD1+ CD8+ exhausted T cells in vivo and in vitro and demonstrate that restoring WNT signaling, by pharmacological blockade of GSK3 beta, can improve effector function. These data unveil novel targets for tumor immunotherapy and have promising implications for the development of a personalized TIL-based cell therapy for lung cancer. CA extern

NAC transcription factors have been characterized in numerous plants, and the NAC gene has been shown to be involved not only in plant growth and development, but also in plant responses to abiotic and biological stresses, such as drought, high salinity, low temperature, and anaerobic/hypoxic stress. Creating an environment of anaerobic/hypoxic stress has been shown to be one of the effective storage methods for delaying the browning of fresh-cut lotus (Nelumbo nucifera) root. However, whether NAC is associated with lotus root browning under anaerobic stress has not been studied. In this study, vacuum packaging (VP; anaerobic/hypoxic stress) effectively delayed the browning of fresh-cut lotus root. The changes in the expressions of NnPAL1, NnPPOA, and NnPOD2/3 were consistent with phenylalanine aminolase, polyphenol oxidase (PPO), and peroxidase (POD) enzyme activity changes and lotus root browning. Using RNA sequencing, five NnNAC genes were isolated and studied. Transcriptional analysis indicates that the NnNAC genes showed different responses to VP. The expressions of NnNAC1/4 were inhibited by VP, which was consistent with the observed change in the degree of fresh-cut lotus root browning. However, NnNAC2 messenger RNA (mRNA) levels were upregulated, and the expressions of NnNAC3/5 showed no clear differences under different packaging scenarios. Thus, NnNAC1/4 were identified as promising candidates for further transcriptional regulation analysis in lotus root to understand more fully the molecular mechanism of browning under anaerobic/anoxic stress.

OBJECTIVE: Yang-deficiency constitution (YADC) is a common unbalanced constitution that predisposes individuals to certain diseases. However, not all people with YADC manifest develop diseases. This calls for delineation of the underlying molecular mechanisms. Previous studies suggested that the gut microbiota and gene differential expression should be considered. METHODS: In the present study, we compared profiles of gut microbiota between four healthy YADC individuals and those of five healthy balanced constitution (BC) counterparts, based on 16S rRNA gene sequence analysis. Furthermore, YADC relevant genes identified by comparing 62 healthy YADC and 58 healthy BC individuals in total to perform intersection analysis, functional clustering and pathway enrichment analyses. RESULTS: The levels of harmful gut microbiota (Prevotellaceae, LDA score > 4.0, P = 0.0141) and beneficial gut microbiota (Ruminococcaceae, LDA score > 4.0, P = 0.0025, Faecalibacterium, LDA score > 4.0, P = 0.0484) were both elevated in healthy YADC individuals. Also, we found that the specific metabolic pathway with 2, 6-Dichloro-p-hydroquinone 1, 2-Dioxygenase (PcpA) as the core in gut microbiota and the glutathione transferase activity has been enriched by YADC relevant genes in healthy YADC individuals were both responsible for the detoxification of halogenated aromatic hydrocarbon substances. CONCLUSIONS: Both beneficial and harmful factors had been detected in healthy YADC individuals, functionally, they may have triggered homeostasis to maintain the health of individuals with YADC. The homeostasis may be maintained by beneficial and harmful factors from gut flora and genes. Future studies are expected to focus on halogenated aromatic hydrocarbons and their detoxification processes.

In this study, by comparing the four groups of sausages, namely, CO (without starter culture), LB (with Lactobacillus sakei), LS (with L. sakei 3X-2B + Staphylococcus xylosus SZ-8), and LSS (with L. sakei 3X-2B + S. xylosus SZ-8 + S. carnosus SZ-2), the effects of mixed starter cultures on physical–chemical quality, proteolysis, and biogenic amines (BAs) during fermentation and ripening were investigated. Inoculation of the mixed starter cultures increased the number of lactic acid bacteria and staphylococci in sausages during fermentation and ripening for 0 to 5 days. The L. sakei 3X-2B + S. xylosus SZ-8 + S. carnosus SZ-2 mixed starter accelerated the rate of acid production and water activity reduction of sausages and improved the redness value. Compared with CO, the mixed starter effectively inhibited Enterobacteriaceae. At the end of ripening, the LSS group was approximately 1.25 CFU/g, which was less than the CO group, thereby reducing the total volatile basic nitrogen (TVB-N) in the LSS group. The free amino acids in the LS and LSS groups (224.97 and 235.53 mg/kg dry sausage, respectively) were significantly (p < 0.001) higher than that in the CO group (170.93 mg/kg dry sausage). The level of histamine, cadaverine, putrescine, and common BAs showed an opposite trend to the increase of the corresponding precursor amino acid content, which were significantly lower (p < 0.001) in the LS and LSS sausages than in CO. This study showed that L. sakei 3X-2B + S. xylosus SZ-8 + S. carnosus SZ-2 is a potential mixed starter for fermented meat products.

Background Metformin is commonly considered the first-line therapy for type 2 diabetes (T2D) and also had potential treating utility in other areas; however, ~20% of patients experience intolerance with unclear underlying mechanisms. In the present study, we performed the full-length 16S rRNA (V1-V9) for the fecal samples and bioinformatics analysis to study the mechanisms of the metformin intolerance combining the gut flora and host. Results The results showed that Barnesiella (p=0.046) and Parabacteroides goldsteinii (p=0.016), which transforming primary into secondary bile acid (SBA), were higher in the TS than T group, and were eliminated in the TSa group, which might lead to the accumulation of primary bile acids (PBA) such as cholic acid (CA), the change of GLI1 gene, and following diarrhea in the TSa group. Lactobacillus brevis (p=0.024) and Lactobacillus plantarum (p=0.026) were up-regulated in TSa than TS group. The two flora might cause the changes of genes including FOXA2, HTR7, GADPH, and intolerance relief, which might be a worthwhile future direction for preventing metformin intolerance. Conclusions These results hinted that the differential flora and co-regulation of them with the host might be intolerance-related. Our results partly provided theoretical support for intolerance prevention.

Ethylene response factor (ERF) genes have been involved in responses to biotic and abiotic stress, including hypoxia and anaerobic stress. Vacuum packaging (a typical anaerobic stress) is an effective storage method used to delay browning of fresh-cut lotus root (Nelumbo nucifera). In model plants, ERF genes have been identified as responsive to hypoxia. Whether ERF is associated with browning of vacuum-packaged lotus root has not been studied. The effects of vacuum packaging on browning, phenolic content, the enzyme activity of phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO), and peroxidase (POD), and PPO, PAL, POD, and ERF genes expression in fresh-cut lotus root were studied. Downregulation of NnPAL1, NnPPOA, and NnPOD2/3 attributable to vacuum packaging coincided with increased related enzyme activities and the degree of browning of fresh-cut lotus root. The expression patterns of NnERF4/5 were consistent with the changes in NnPAL1, NnPPOA, and NnPOD2/3 gene expression. It has been proposed that NnERF4/5 could have be important regulators of fresh-cut lotus root browning, and that the relationships of NnERF4/5 and NnPAL1, NnPPOA, and NnPOD2/3 should to be studied further.

Although Walnut oil (WO) has been reported to enhance cognitive function, the underlying molecular mechanisms are not well understood. This study was designed to assess the effects of WO on spatial memory in rats through modulation of the expression of acid‐sensing ion channel genes, Asic2a and Asic4. To investigate the effect of WO on cognitive performance, we supplemented the diet of female rats with WO. The results showed that supplementation with WO at doses of 2.2 and 11 g kg−1 day−1 significantly improved learning and memory. In vitro treatment of rat hippocampal neuronal cells with appropriate doses of WO revealed a significant increase in the expression of Asic2a and Asic4 in a dose‐dependent manner at both the mRNA and protein levels. We conclude that WO intake might help to prevent cognitive decline, particularly in the elderly, and that ASIC genes in neurons can be the targets of compounds contained in the oil.

Vibrio parahaemolyticus is one of the most common pathogenic bacteria that pose a threat to human health. The purpose of this study was to investigate antibacterial mechanisms of ε-poly-lysine (ε-PL) against V. parahaemolyticus using a lable free-based proteomic analysis. The differentially expressed proteins (DEPs) were subjected to bioinformatics analysis. The results indicated that a total of 196 DEPs, including 118 up-regulated and 78 down-regulated, were identified in the ε-PL-treated cells compared with control group. Upon Go functional enrichment, 13, 9, and 8 specific Go terms in biological processes, molecular functions and cellular components were identified, respectively. KEGG pathways analysis indicated that the DEPs were mainly involved in bacterial chemotaxis, RNA transport and two-component system, which were significantly enriched (P 0.05). In PPI analysis, Che R and Che V, both involved in bacterial chemotaxis and RNA transport pathways, are closely related to other DEPs. Therefore, the down-regulation of Che R and Che V in ε-PL-treated cells resulted in the reduction or even loss of bacterial adaptability, and they were the critical action sites of ε-PL to inactivate V. parahaemolyticus.

Energy management strategy is developed by considering the random and air conditioning load fluctuation, which greatly affected the torque control of the electric motor in electric vehicle. Firstly, the vehicle power consumption model is established, based on the influencing factors of electric vehicle energy consumption: random load and air conditioning load. Therefore, driving conditions with random characteristics representing the actual random load are constructed. According to the clustered characteristic parameters, the driving conditions were classified as different driving modes. Secondly, the mode of predicted condition was taken as a variable to evaluate the logic threshold strategy and fuzzy control strategy in which the influence of air conditioning was considered. Finally, under the condition of New European Driving Cycle (NEDC), the proposed management strategy was simulated in software environment, and the hardware in-loop (HIL) test was performed to verify the strategy. The simulation and HIL test results show that the proposed energy management strategy can increase the driving range by considering the load fluctuation of air conditioning. Furthermore, the strategy combining the driving mode prediction can alleviate the decline rate of SOC. And the fuzzy control strategy has better adaptability in complex conditions and lower battery energy consumption rate.

We consider representation learning of 3D molecular graphs in which each atom is associated with a spatial position in 3D. This is an under-explored area of research, and a principled message passing framework is currently lacking. In this work, we conduct analyses in the spherical coordinate system (SCS) for the complete identification of 3D graph structures. Based on such observations, we propose the spherical message passing (SMP) as a novel and powerful scheme for 3D molecular learning. SMP dramatically reduces training complexity, enabling it to perform efficiently on large-scale molecules. In addition, SMP is capable of distinguishing almost all molecular structures, and the uncovered cases may not exist in practice. Based on meaningful physically-based representations of 3D information, we further propose the SphereNet for 3D molecular learning. Experimental results demonstrate that the use of meaningful 3D information in SphereNet leads to significant performance improvements in prediction tasks. Our results also demonstrate the advantages of SphereNet in terms of capability, efficiency, and scalability. Our code is publicly available as part of the DIG library (https://github.com/divelab/DIG)., Comment: The paper has been accepted by ICLR 2022. You can also cite the conference version

Molecular property prediction is gaining increasing attention due to its diverse applications. One task of particular interests and importance is to predict quantum chemical properties without 3D equilibrium structures. This is practically favorable since obtaining 3D equilibrium structures requires extremely expensive calculations. In this work, we design a deep graph neural network to predict quantum properties by directly learning from 2D molecular graphs. In addition, we propose a 3D graph neural network to learn from low-cost conformer sets, which can be obtained with open-source tools using an affordable budget. We employ our methods to participate in the 2021 KDD Cup on OGB Large-Scale Challenge (OGB-LSC), which aims to predict the HOMO-LUMO energy gap of molecules. Final evaluation results reveal that we are one of the winners with a mean absolute error of 0.1235 on the holdout test set. Our implementation is available as part of the MoleculeX package (https://github.com/divelab/MoleculeX)., Comment: One of the winners of 2021 KDD Cup on OGB Large-Scale Challenge

Additional file 1: Sup Fig. 1. Typical sample of schistosomiasis-associated colorectal cancer, the red arrows indicate schistosome ova (HE, ��100). Sup Fig. 2. Determination of cut-off values of CD8 density of TMAs and survival analyses. X-tile analysis of OS was performed using patients��� data collected from the pathological system of the Qingpu District Center for Disease Control and Prevention. The optimal cut-off values highlighted by the black circles in left panels are shown in histograms of the entire cohort (middle panels), and Kaplan-Meier plots are displayed in right panels. . The optimum cutoff value of CD8+T cell density were determined by X-tile program, which were 279 (��2 = 15.538, p = 0.0029) cell/mm2. CD8low group was defined as CD8+ T cells density

The quality of fresh-cut lotus root slices is greatly affected by enzymatic browning. In this study, we investigated the effects of 1-methylcyclopropene treatment on browning and quality deterioration of lotus root slices. When fresh-cut lotus root slices were immersed in 0.1 mg L−1 1-MCP for 1 h and stored at 10 ℃ for twelve days, microbial growth, respiration, total phenolic content, phenylalanine ammonia lyase activity, polyphenol oxidase activity, and soluble quinone levels in fresh-cut lotus root slices were suppressed. Furthermore, 1-MCP treatment improved the antioxidant capacities, peroxidase activities, superoxide dismutase activities, catalase activities, and DPPH free radical scavenging rates in fresh-cut lotus root slices. In addition, 1-MCP treatment inhibited the production of reactive oxide species, which delayed quality deterioration of fresh-cut lotus root slices. Based on transcriptomics and real-time quantitative PCR results, gene expression levels of NnmetK2, NnACO, NnETR2, NnEIN3, and NnERF1 were up-regulated while expression levels of NnEBF1 were down-regulated. These findings indicate that 1-MCP inhibits ethylene biosynthesis and signal transduction, which suppresses a series of ethylene-induced physiological and biochemical reactions. Based on our findings, we propose a new strategy for inhibiting enzymatic browning in fresh-cut lotus root slices.

5-Methoxyleoligin and leoligin are natural occurring lignans derived from Edelweiss (Leontopodium nivale ssp. alpinum), displaying potent pro-angiogenic and pro-arteriogenic activity. Cholesterol efflux from macrophages is associated with reverse cholesterol transport which inhibits the development of cardiovascular disease. Within this study, we developed a modular and stereoselective total synthesis of 5-methoxyleoligin which can be readily used to prepare a novel compound library of related analogs. The target 5-methoxyleoligin was synthesized exploiting a recently disclosed modular route, which allows also rapid synthesis of analogous compounds. All obtained products were tested towards macrophage cholesterol efflux enhancement and the performance was compared to the parent compound leoligin. It was found that variation on the aryl moiety in 2-position of the furan ring allows optimization of the activity profile, whereas the ester-functionality does not tolerate significant alterations.

AimTo establish a gene co-expression network for identifying principal modules and hub genes that are associated with drought resistance mechanisms, analyzing their mechanisms, and exploring candidate genes.Methods and findings42 data sets including PRJNA380841 and PRJNA369686 were used to construct the co-expression network through weighted gene co-expression network analysis (WGCNA). A total of 1,896,897,901 (284.30 Gb) clean reads and 35,021 differentially expressed genes (DEGs) were obtained from 42 samples. Functional enrichment analysis indicated that photosynthesis, DNA replication, glycolysis/gluconeogenesis, starch and sucrose metabolism, arginine and proline metabolism, and cell cycle were significantly influenced by drought stress. Furthermore, the DEGs with similar expression patterns, detected by K-means clustering, were grouped into 29 clusters. Genes involved in the modules, such as dark turquoise, yellow, and brown, were found to be appreciably linked with drought resistance. Twelve central, greatly correlated genes in stage-specific modules were subsequently confirmed and validated at the transcription levels, including TraesCS7D01G417600.1 (PP2C), TraesCS5B01G565300.1 (ERF), TraesCS4A01G068200.1 (HSP), TraesCS2D01G033200.1 (HSP90), TraesCS6B01G425300.1 (RBD), TraesCS7A01G499200.1 (P450), TraesCS4A01G118400.1 (MYB), TraesCS2B01G415500.1 (STK), TraesCS1A01G129300.1 (MYB), TraesCS2D01G326900.1 (ALDH), TraesCS3D01G227400.1 (WRKY), and TraesCS3B01G144800.1 (GT).ConclusionsAnalyzing the response of wheat to drought stress during different growth stages, we have detected three modules and 12 hub genes that are associated with drought resistance mechanisms, and five of those genes are newly identified for drought resistance. The references provided by these modules will promote the understanding of the drought-resistance mechanism. In addition, the candidate genes can be used as a basis of transgenic or molecular marker-assisted selection for improving the drought resistance and increasing the yields of wheat.

The effects of storage condition on the physicochemical characteristics of sunflower seed oil (SSO) were investigated, to understand the required conditions and the typical indicators for its quality control. The changes of SSO in peroxide value (PV), acid value (AV), fatty acid (FA) composition, Fourier transform infrared (FTIR) spectrum and volatile compound (VC) during 11 month storage under seven different conditions, were analyzed. The PVs and AVs of the seven groups all increased with time, but the PVs fluctuated strongly during the last 4 months. The between-group differences in PV and AV indicated that light-exposure and high-temperature (≥40 °C) both accelerated the production and degradation of primary oxidation products of FA. However, the FA composition of SSO did not obviously change regardless of storage condition and time, as well as its FTIR characteristics. By contrast, its VC composition was significantly changed by light-exposure and high-temperature (≥55 °C). 3-Methyl-2,5-furandione, acetic acid/1-phenylethyl ester, 2-pentyl-furan and limonene might be the main VCs related to the desirable flavor, in which 3-methyl-2,5-furandione in all the groups showed a significantly decreased percentage of VC composition during storage. Light-exposure and high-temperature enhanced the accumulation of aldehydes, especially hexanal and (E)-2-heptenal, which principally contributed to the undesirable flavor of SSO. 3-Methyl-2,5-furandione, hexanal and (E)-2-heptenal were proposed to be marker compounds for its quality control. A low-temperature and dark condition is necessary for SSO to remain a desirable flavor.

The in vitro activities of 39 polysaccharides from different parts of 13 lotus root varieties were evaluated and introduced into multiple linear regression analysis to explore the structure-activity relationships using their chromatographic fingerprint features as independent variables. Their 2,2-diphenyl-1-picrylhydrazyl/hydroxyl radical scavenging abilities, ferric reducing antioxidant powers and growth-inhibitory effects against HepG2 and SGC7901 cancer cells were all diverse, with the variable-coefficients ranging from 24.49% to 87.76%, while their macrophage immunostimulatory activities evaluated by nitric oxide production and tumor necrosis factor-alpha secretion showed relatively low variations. Lotus root polysaccharides (LRPs) from the peels and nodes possessed stronger activities than those from the fleshes. Their fingerprint-activity relationship models indicated that monosaccharide composition was closely related to the activities, but not molecular weight. LRPs have health-improving potentials, and their activities can be partly predicted by the quantitative fingerprint-activity relationship model.

Lotus root (Nelumbo nucifera G.) is a high economic value crop in the world. In this study, the storage characteristics (color, sensory, texture, and fatty acids) of lotus root (“Elian No.5″) were evaluated at different harvest periods (September 2018, October 2018, November 2018, December 2018, and January 2019). Moreover, the storage characteristics were evaluated after the short- term and long-term storage of lotus root at 4 °C and 20 °C. The hardness of lotus root significantly decreased at both temperatures (4 °C and 20 °C) during the first 3 days of storage. In contrast, the decrease in hardness delayed at 4 °C (beyond 3 days of storage). Further, genes related to hardness at different storage temperatures were identified using the RNA-seq and qRT-PCR. The results of this study provide a reference for lotus root storage and a basis for the molecular breeding of longterm-storable lotus root.

In order to improve the contour tracking performance of the direct-drive H-type platform, a control strategy combining the ideal integral error dynamic (IIED) position controller with the variable gain cross-coupling compensator is proposed.IIED position controller is used to improve tracking performance of linear motor servo system.A new real-time contour error estimation model is established based on the relationship between tracking error and contour error, and the effect of synchronization error is eliminated by coordinate correction to further improve the estimation accuracy. Combined with the improved variable gain cross coupling control structure, a contour error compensator is designed. Simulation results show that the proposed control strategy can not only estimate the contour error of H-type platform, but also improve the tracking accuracy and contour control accuracy.

Forty-one sunflower seed oil (SSO) products were collected to investigate their quality parameters before and after high-temperature and short-time (HTST) cooking, including peroxide value (PV), acid value (AV) and fatty acid (FA) composition. Their Fourier-transform infrared (FTIR) spectra were then scanned to explore the parameter-FTIR characteristic relationship using chemometrics with multiple linear regression (MLR) analysis. The PV and AV of uncooked products were in the range of 1.49–6.29 mmol kg−1 and 0.04–0.31 mg g−1, with the variation coefficient of 36.47% and 146.82%, respectively. They were mainly composed of palmitic acid (2.39–3.33%), stearic acid (1.76–2.54%), oleic acid (10.02–24.77%) and linoleic acid (66.42–83.62%). The parameter changes caused by HTST cooking were slight. SSO products from different countries might have significantly different FA composition, especially linoleic acid content (P < 0.05), and those with different shelf times might differ in PV (P < 0.05). In addition, the FTIR spectra of cooked and uncooked SSO showed the similarity degree values ranging from 0.67 to 0.97 and 0.72 to 0.97, respectively. All the spectra exhibited the characteristic bands of –C–H, –CO, –C–O– and CH2, in which 11 common bands as independent variables were selected to establish various FTIR characteristic–quality relationship models. The models of palmitic acid, oleic acid and linoleic acid were acceptable for their content predictions. Moreover, the cooked oils and uncooked oils could be completely distinguished by orthogonal partial least squares discriminant analysis due to the cooking-caused changes in FTIR spectrum. Production place and shelf time were the important factors related to the quality diversity of SSO, and FTIR spectroscopy combined with chemometrics was feasible for the simultaneous determination of various quality parameters.

A recurrent wavelet fuzzy neural network (RWFNN) control method combined with global sliding mode control (GSMC) is proposed to solve the problem of dual-axis synchronous error of H-type platform system driven by permanent magnet synchronous linear motor. Firstly, global sliding mode controller is designed to eliminate the approaching mode, reduce tracking error and ensure global robustness in the single-axis of H-type platform system. Recurrent wavelet fuzzy neural network compensator is designed for the dual-axis of H-type platform system, to compensate the synchronous error. The simulation results show that the proposed method not only guarantees the global robustness of the system, but also effectively reduces the synchronous error of the system and improves the tracking accuracy.

The tracking error in the iterative learning control (ILC) process of the permanent magnet linear synchronous motor (PMLSM) servo system can be decomposed into learnable and divergent components by the empirical mode decomposition (EMD) algorithm. The problem of slow convergence or even divergence due to the accumulation of tracking errors in each iteration was solved by eliminating the divergent components. However when the PMLSM system is disturbed by measuring noise, it can easily lead to mode mixing, compromising the accuracy of the decomposition. In this paper, modified ensemble empirical mode decomposition (MEEMD) algorithm is used to decompose the tracking error. The algorithm is combined with the detection of signal randomness based on permutation entropy (PE). Firstly, a suitable PE threshold is set up to remove measuring noise, and then the residual effective tracking errors signal is decomposed by EMD algorithm. Finally the divergent components are found and eliminated. From the simulation results, the divergent components are screened and eliminated more accurately, the phenomenon of mode mixing is avoided effectively, the number of iterations is reduced, the convergence speed and tracking accuracy of PMLSM servo system are improved.

Limei Wang,1,2 Jin Pei,1 Zhongcheng Cong,1 Yifang Zou,1 Tianmeng Sun,3 Fionán Davitt,4,5 Adrià Garcia-Gil,4,5 Justin D Holmes,4,5 Caitriona M O’Driscoll,6 Kamil Rahme,4,7 Jianfeng Guo1 1School of Pharmaceutical Sciences, Jilin University, Changchun 130021, China; 2Department of Pharmacy, The General Hospital of FAW, Changchun 130011, China; 3The First Hospital of Jilin University, Changchun 130021, China; 4School of Chemistry and the Tyndall National Institute, University College Cork, Cork, Ireland; 5CRANN, Trinity College Dublin, Dublin, Ireland; 6Pharmacodelivery Group, School of Pharmacy, University College Cork, Cork, Ireland; 7Department of Sciences, Faculty of Natural and Applied Science, Notre Dame University (Louaize), Zouk Mosbeh 1200, Lebanon Background: Gold nanorods (AuNRs), due to the optical and electronic properties namely the surface plasma resonance, have been developed to achieve the light-mediated photothermal therapy (PTT) for cancer. However, PTT alone may suffer from inefficient tumor killing. Recently, the combination of PTT and chemotherapy has been utilized to achieve synergistic anticancer effects. Methods: In this study, AuNRs capped with hexadecyltrimethylammonium bromide (CTAB), poly(acrylic acid) (PAA), and PEGylated anisamide (a ligand known to target the sigma receptor) have been developed to produce a range of negatively charged anisamide-targeted PEGylated AuNRs (namely Au-CTAB-PAA-PEG-AA) for the combination of PTT and chemotherapy (termed as chemo-photothermal therapy [CPTT]). Epirubicin (EPI, an anthracycline drug) was efficiently loaded onto the surface of Au800-CTAB-PAA-PEG-AA via the electrostatic interaction forming Au800-CTAB-PAA-PEG-AA.EPI complex. Results: The resultant complex demonstrated pH-dependent drug release, facilitated nucleus trafficking of EPI, and induced antiproliferative effects in human prostate cancer PC-3 cells. When Au800-CTAB-PAA-PEG-AA.EPI complex was further stimulated with desired laser irradiation, the synergistic outcome was evident in PC-3 xenograft mice. Conclusion: These results demonstrate a promising strategy for clinical application of CPTT in cancer. Keywords: gold nanoparticles, non-viral drug delivery, chemotherapy, photothermal therapy, synergistic effect

To investigate the structure, in vitro digestibility and activity of polysaccharides from lotus root, their main fractions named LRPs were isolated and purified by gel filtration chromatography. Structural analyses indicated that: LRPs were α‑(1 → 6)‑ d ‑heteroglucans mainly composed of Glc-(1→, →6)-Glc-(1→, →6)-Gal-(1→, →4,6)-Gal-(1→ and →3,6)-Glc-(1→ at a molar ratio of 1.00: 4.33: 0.83: 0.13: 1.14; the total molar percentage of other monosaccharides in LRPs, including Man, Rha, GalA and Ara, was 8.10%; the molecular weights of LRPs was in the range of 1.33 kDa to 5.30 kDa. According to the change of molecular weight and the productions of reducing sugar and free monosaccharide, the simulated experiments of salivary, gastric and intestinal digestion confirmed that LRPs were almost undigestible. Moreover, LRPs showed the scavenging ability against DPPH and hydroxyl radicals, the growth inhibition ability against SGC7901 and HepG2 cancer cells in vitro, and the immunostimulating effect on the NO and TNF-α productions of macrophages in vitro. LRPs nearly remain their initial structure and activities in upper gastrointestinal tract and have health-improving potentials.

We report on Rydberg spectroscopy of ultracold atoms in an atom-ion hybrid trap for probing the electric fields in a mixture of atoms and ions. We obtain spectra which exhibit excitation gaps corresponding to avoided level crossings in the Stark map. From these measurements we can conclude that the ground state atoms experience electrical fields of up to 250 V/cm. There is, however, a difficulty in interpreting the results, because some data indicate that the electrical fields are produced by the ions while other data indicate that they stem from the Paul trap. We discuss possible scenarios for explaining the measured data, provide first measurements to check these scenarios, and propose methods to finally solve this puzzle., Comment: 5 pages, 5 figures

Leoligin is a natural lignan found in Edelweiss (Leontopodium nivale ssp. alpinum). The aim of this study was to examine its influence on cholesterol efflux and to address the underlying mechanism of action. Leoligin increases apo A1- as well as 1% human plasma-mediated cholesterol efflux in THP-1 macrophages without affecting cell viability as determined by resazurin conversion. Western blot analysis revealed that the protein levels of the cholesterol efflux transporters ABCA1 and ABCG1 were upregulated, whereas the SR-B1 protein level remained unchanged upon treatment with leoligin (10 μM, 24 h). Quantitative reverse transcription PCR further uncovered that leoligin also increased ABCA1 and ABCG1 mRNA levels without affecting the half-life of the two mRNAs in the presence of actinomycin D, a transcription inhibitor. Proteome analysis revealed the modulation of protein expression fingerprint in the presence of leoligin. Taken together, these results suggest that leoligin induces cholesterol efflux in THP-1-derived macrophages by upregulating ABCA1 and ABCG1 expression. This novel activity suggests leoligin as a promising candidate for further studies addressing a possible preventive or therapeutic application in the context of atherosclerosis.

Medicinal plants have historically proven their value as a source of molecules with therapeutic potential, and nowadays still represent an important pool for the identification of novel drug leads. In the past decades, pharmaceutical industry focused mainly on libraries of synthetic compounds as drug discovery source. They are comparably easy to produce and resupply, and demonstrate good compatibility with established high throughput screening (HTS) platforms. However, at the same time there has been a declining trend in the number of new drugs reaching the market, raising renewed scientific interest in drug discovery from natural sources, despite of its known challenges. In this survey, a brief outline of historical development is provided together with a comprehensive overview of used approaches and recent developments relevant to plant-derived natural product drug discovery. Associated challenges and major strengths of natural product-based drug discovery are critically discussed. A snapshot of the advanced plant-derived natural products that are currently in actively recruiting clinical trials is also presented. Importantly, the transition of a natural compound from a “screening hit” through a “drug lead” to a “marketed drug” is associated with increasingly challenging demands for compound amount, which often cannot be met by re-isolation from the respective plant sources. In this regard, existing alternatives for resupply are also discussed, including different biotechnology approaches and total organic synthesis.While the intrinsic complexity of natural product-based drug discovery necessitates highly integrated interdisciplinary approaches, the reviewed scientific developments, recent technological advances, and research trends clearly indicate that natural products will be among the most important sources of new drugs also in the future.

The preparation mainly composed of extraction, pre-purification and dehydration is essential for the research and development of natural polysaccharides. The methods or conditions used in the three procedures had significant effects on the composition, structure and function of the polysaccharides obtained. Temperature, pH, enzyme, ultrasound and microwave were the important factors associated with their physicochemical changes. Molecular degradation and intermolecular interaction were two of the main mechanisms responsible for the changes. The degradations of polysaccharides responding to hydrothermal and ultrasonic conditions could be partly descripted by multiple linear regression model, implying the possibility for the prediction and control of polysaccharide degradation. Moreover, the interactions between polysaccharide and other compounds, forming complexes natively or conditionally, could be selectively triggered or eliminated to obtain polysaccharides under certain functions. This work shows new insights into the preparation of polysaccharides, which could benefit the efficient utilization of their natural and modified properties.

For the contouring errors produced by repetitive tracking motion of single-axis linear motor on XY platform, a combined method of fractional iterative learning and cross coupled is proposed. Firstly, a positional controller of the fractional PD-type iterative learning is designed, and the integer differential operator is replaced by the differential operator defined by Grunwald-Letnikov fractional calculus to improve the traditional integer order iterative learning law. The convergence condition of the fractional iterative learning controller is given. Then, the cross-coupled control is adopted between two axes, and the contour error is estimated by using the real-time contour error estimation model to reduce the contour error. The compensation amount of X and Y axis is assigned according to the relationship of cross-coupled gain, and the real-time compensation. The simulation shows that compared with integral iterative learning, fractional iterative learning has faster convergent speed and higher accuracy of contouring process. Fractional iterative learning is an effective way to improve the contour error.

A high performance size exclusion-fluorescence detection (HPSEC-FD) method combined with fluorescein isothiocyanate (FITC) prelabeling was established for the microanalysis of polysaccharide–protein complexes from longan pulp (LPP). FITC-labeled LPP (LPPF) was fractionated by gel filtration chromatography. The weight-average molecular weight and FITC substitution degree of LPPF were 39.01 kDa and 0.20%, respectively. The HPSEC-FD calibration curves linear over the range of 1–200 µg/mL in mouse plasma, spleen and lung samples with correlation coefficients greater than 0.995. The inter-day and intra-day precisions of the method were not more than 6.9%, and the relative recovery ranged from 93.7% to 106.4%. The concentration–time curve of LPPF in plasma following intravenous (i.v.) administration at 40 mg/kg body weight well fitted to a two-compartment model. LPPF rapidly eliminated from plasma according to the short half-lives (t1/2α = 2.23 min, t1/2β = 39.11 min) and mean retention times (MRT0–t = 1.15 h, MRT0–∞ = 1.39 h). After administration over 5 to 360 min, the concentration of LPPF in spleen homogenate decreased from 7.41 to 3.68 µg/mL, the concentration in lung homogenate decreased from 9.08 to 3.40 µg/mL. On the other hand, the increasing concentration of LPPF fraction with low molecular weight in heart homogenate was observed.

The Da’an-Dedu Fault Zone is a major tectonic feature cutting through the Songliao Basin from south to north in NE China. Five earthquakes with magnitudes over 5 that occurred during the past 30 years suggest the fault zone is a seismogenic structure with future seismic potential. The structural pattern, tectonic history, Quaternary activity and seismic potential have previously been unknown due to the Quaternary sedimentary coverage and lack of large historic earthquakes ( M > 7). In this paper, we use seismic reflection profiles and drilling from petroleum explorations and shallow-depth seismic reflections to study those problems. The total length of the Da’an-Dedu Fault Zone is more than 400 km; modern seismicity delineates it into 4 segments each with a length of 90–100 km. In cross-section view, the folds and associated faults form a complex structural belt with a width of more than 10 km. Shallow-level seismic reflection across the Da’an-Dedu Fault Zone reveals that the Late Quaternary sediments were folded and faulted, indicating its present tectonic activity. The Da’an-Dedu Fault Zone and Songliao Basin have been subjected to three stages of tectonic evolution: a rifting stage characterized by normal faulting and extension (∼145–112 Ma), a prolonged stage of thermal subsidence (∼112–65 Ma), and a tectonic reversal that has been taking place since ∼65 Ma. Our shallow-level reflection profiles show that the folding and reverse faulting have influenced the Late Quaternary sediments. The seismicity and moderate earthquakes suggest that the tectonic activity persists today. The deformation rate across the Da’an-Dedu Fault Zone, however, is measured to be very slow. In conjunction with the inference that most deformation in NE China may be taken up by the Yilan-Yitong Fault Zone bounding the Songliao Basin to the east, we suggest moderate earthquake potential and thus moderate seismic hazards along the Da’an-Dedu Fault Zone. The geological structures, which include anticlines and reverse faults, imply that the Da’an-Dedu Fault Zone has been a contractive structure since ∼65 Ma, and this type of contraction dominates the tectonic deformation in the Songliao Basin and the entire NE China, although the reasons for these conditions need to be further studied.

We report increased cholesterol efflux from macrophages in the presence of falcarindiol, an important dietary constituent present in commonly used vegetables and medicinal plants. Falcarindiol (3-20 μM) increased cholesterol efflux from THP-1-derived macrophages. Western blot analysis showed an increased protein level of ABCA1 upon falcarindiol exposure. Quantitative real-time PCR revealed that also ABCA1 mRNA level rise with falcarindiol (10 μM) treatment. The effect of falcarindiol on ABCA1 protein as well as mRNA level were counteracted by co-treatment with BADGE, an antagonist of PPARγ. Furthermore, falcarindiol significantly inhibited ABCA1 protein degradation in the presence of cycloheximide. This post-translational regulation of ABCA1 by falcarindiol occurs most likely by inhibition of lysosomal cathepsins, resulting in decreased proteolysis and extended protein half-life of ABCA1. Taken together, falcarindiol increases ABCA1 protein level by two complementary mechanisms, i.e., promoting ABCA1 gene expression and inhibiting ABCA1 protein degradation, which lead to enhanced cholesterol efflux.

A sliding mode robust control based on HJI theory is proposed for the synchronous control of the H-type precision motion platform driven by the dual linear motors. Although the same control method is operating on two Permanent Magnet Linear Synchronous Motors (PMLSM) with identical parameters. The synchronous error between the two motors is unavoidable due to the unbalanced forces, mechanical assembly variations, and various disturbances during the working process. The synchronous error will affect the quality of the workpieces and even lead to a stop of the working process due to over current protection. In this paper, the dynamic model of single-axis motion control system with a lumped uncertainty, which comprises parameter variations, external disturbances, and nonlinear friction force, is introduced first. The sliding mode robust control based on HJI theory is proposed for the single axis of the H-type precision motion platform, by designing the Lyapunov function and the sliding mode control law of the control system to satisfy the HJI theory, so that the robust condition is guaranteed. It can be concluded from simulation results, sliding mode robust control based on HJI theory can improve the tracking accuracy of the single axis and ensure synchronous error converge to zero. This indicates that tracking performance and robustness of the system is improved.

An interval type-2 fuzzy neural network(IT2FNN) control method is presented for H-type gantry stage driven by dual linear motors. The synchronous motion of the dual linear motors is the main factor affecting the accuracy and robustness of the servo system. Thus, the proposed method sets the position error of the both side motors as input, the powerful self-learning ability of neural network is used to guarantee the synchronous error converge to zero to achieve synchronous control. From the simulation results, the synchronous performance of the two-axis motion is significantly improved, and the robustness can be obtained as well using the proposed IT2FNN control method.

Dynamic surface backstepping sliding mode position control method of permanent magnet linear synchronous motor (PMLSM) was presented in this paper. The influence of uncertainties such as parameter variations, load disturbances, end effect and friction, on the performance of PMLSM was considered. Based on the mathematical model of PMLSM and backstepping sliding mode theory, the position controller was designed by combining the backstepping design method and sliding mode control. The concept of virtual command was introduced. There is a weakness in backstepping method that is a complexity of control law caused by achieving the derivation of the virtual control. Dynamic surface control method solved this problem by calculating the derivative of the virtual control using the first-order integral filter. The stability analysis of the controller of PMLSM was achieved by Lyapunov function. Simulation results show that the influence on system performance of uncertainties can be effectively restrained. The design of controller and parameters were simple and the proposed controller ensured the robustness and tracking speed of PMLSM control system. The chattering phenomenon of sliding mode control has been effectively suppressed.

Cholesterol efflux (ChE) from macrophages is an initial step of reverse cholesterol transport (RCT). The ATP-binding cassette transporter A1 (ABCA1) is a key transporter for ChE and its increased expression is regarded to attenuate atherosclerosis. Thus, the identification and characterization of molecules raising ABCA1 and thereby stimulating ChE is of pharmacological relevance. In this study, we tested dietary compounds from olive oil for their capacity of enhancing cellular ABCA1 protein level. We identified erythrodiol (Olean-12-ene-3β,28-diol) as an ABCA1 stabilizer and revealed its positive influence on ChE in THP-1-derived human macrophages. Among the nine tested compounds from olive oil, erythrodiol was the sole compound raising ABCA1 protein level (at 10 μM). None of the tested compounds impaired viability of THP-1 macrophages from 5 to 20 μM as determined by resazurin conversion. Western blot analyses of key membrane transporters contributing to ChE showed that the protein level of ABCG1 and scavenger receptor class B member 1 (SR-B1) remain unaffected by erythrodiol. Besides, erythrodiol (10 μM) did not influence the mRNA level of ABCA1, ABCG1, and SR-B1, as determined by quantitative reverse transcription PCR, but significantly inhibited the degradation of ABCA1 as evident by an increased half-life of the protein in the presence of cycloheximide, an inhibitor of de novo protein synthesis. Therefore, erythrodiol promotes ChE from THP-1-derived human macrophages by stabilizing the ABCA1 protein. This bioactivity makes erythrodiol a good candidate to be further explored for therapeutic or preventive application in the context of atherosclerosis.

The research shows that the increase of the strength of reinforcing bars can effectively improve the bearing capacity of the components, reduce the amount of reinforcing bars and decrease the difficulty of construction. At present, the yield strength of high-performance reinforcing bars developed abroad and applied in practical engineering is 400–900 MPa, while that in China has reached 700 MPa. As strain-rate sensitive materials, the strain-rate effect of reinforcing bars should be taken into account in the design of seismic buildings and explosion-resistant protective structures. In order to figure out the strain-rate effect of HTRB700, the properties of HRB400 and HTRB700 reinforcing bars are tested. Their performance mechanism and strain-rate response are studied respectively. Among them, the strain rate range of strain-rate effect experiments is 2.5×10−4–100 s−1. The calculation formula is obtained after fitting and analyzing the experimental results, which provides information for the popularization and application of HTRB700 reinforcing bars with new high strength and high plasticity in seismic and explosion resistant structures.