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While metal nanoparticles (NPs) have demonstrated their great potential in catalysis, introducing chiral microenvironment around metal NPs to achieve efficient conversion and high enantioselectivity remains a long-standing challenge. In this work, tiny Rh NPs, modified by chiral diene ligands (Lx) bearing diverse functional groups, are incorporated into a covalent organic framework (COF) for the asymmetric 1,4-addition reactions between arylboronic acids and nitroalkenes. Though Rh NPs hosted in the COF are inactive, decorating Rh NPs with Lx creates the active Rh-Lx interface and induces high activity. Moreover, chiral microenvironment modulation around Rh NPs by altering the groups on chiral diene ligands greatly optimizes the enantioselectivity (up to 95.6% ee). Mechanistic investigations indicate that the formation of hydrogen-bonding interaction between Lx and nitroalkenes plays critical roles in the resulting enantioselectivity. This work highlights the significance of chiral microenvironment modulation around metal NPs by chiral ligand decoration for heterogeneous asymmetric catalysis.
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Inspired by enzymatic catalysis, it is crucial to construct hydrogen-bonding-rich microenvironment around catalytic sites; unfortunately, its precise construction and understanding how the distance between such microenvironment and catalytic sites affects the catalysis remain significantly challenging. In this work, a series of metal-organic framework (MOF)-based single-atom Ru1 catalysts, namely, Ru1/UiO-67-X (X = -H, -m-(NH2)2, -o-(NH2)2), have been synthesized, where the distance between the hydrogen-bonding microenvironment and Ru1 sites is modulated by altering the location of amino groups. The -NH2 group can form hydrogen bonds with H2O, constituting a unique microenvironment that causes an increased water concentration around the Ru1 sites. Remarkably, Ru1/UiO-67-o-(NH2)2 displays a superior photocatalytic hydrogen production rate, â¼4.6 and â¼146.6 times of Ru1/UiO-67-m-(NH2)2 and Ru1/UiO-67, respectively. Both experimental and computational results suggest that the close proximity of amino groups to the Ru1 sites in Ru1/UiO-67-o-(NH2)2 improves charge transfer and H2O dissociation, accounting for the promoted photocatalytic hydrogen production.
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While supported metal nanoparticles (NPs) have shown significant promise in heterogeneous catalysis, precise control over their interaction with the support, which profoundly impacts their catalytic performance, remains a significant challenge. In this study, Pt NPs are incorporated into thioether-functionalized covalent organic frameworks (denoted COF-Sx), enabling precise control over the size and electronic state of Pt NPs by adjusting the thioether density dangling on the COF pore walls. Notably, the resulting Pt@COF-Sx demonstrate exceptional selectivity (> 99 %) in catalytic hydrogenation of p-chloronitrobenzene to p-chloroaniline, in sharp contrast to the poor selectivity of Pt NPs embedded in thioether-free COFs. Furthermore, the conversion over Pt@COF-Sx exhibits a volcano-type curve as the thioether density increases, due to the corresponding change of accessible Pt sites. This work provides an effective approach to regulating the catalysis of metal NPs via their microenvironment modulation, with the aid of rational design and precise tailoring of support structure.
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The soil contains abundant and diverse microorganisms, which interrelate closely with the aboveground vegetation and impact the structure and function of the forest ecosystem. To explore the effect of vegetation diversity on soil microbial functional diversity in taiga forests, we selected significantly different important values of Larix gmelinii as experimental grouping treatments based on plant investigation from fixed plots in Da Xing'anling Mountains. Following that, we collected soil samples and applied the Biolog-ECO microplate method to investigate differences in carbon source utilization, features of functional diversity in soil microorganisms, and factors influencing them in taiga forests. The AWCD decreased as the important value of Larix gmelinii grew, and soil microorganisms preferred carboxylic acids, amino acids, and carbohydrates over polymers, phenolic acids, and amines. The Shannon and McIntosh indexes decreased significantly with the increase of the important value of Larix gmelinii (p < 0.05) and were positively correlated with soil SOC, MBC, C/N, and pH, but negatively with TN, AP, and AN. Redundancy analysis revealed significant effects on soil microbial functional diversity from soil C/N, SOC, AP, MBC, TN, pH, AN, and WC. To sum up, heterogeneous habitats of taiga forests with different important values altered soil microbial functional diversity.
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The poor hydrostability of most reported metal-organic frameworks (MOFs) has become a daunting challenge in their practical applications. Recently, MOFs combined with multifunctional polymers can act as a functional platform and exhibit unique catalytic performance; they can not only inherit the outstanding properties of the two components but also offer unique synergistic effects. Herein, an original porous polymer-confined strategy has been developed to prepare a superhydrophobic MOF composite to significantly enhance its moisture or water resistance. The selective nucleation and growth of MOF nanocrystals confined in the pore of PDVB-vim are closely related to the structure-directing and coordination-modulating properties of PDVB-vim. The resultant MOF/PDVB-vim composite not only produces superior superhydrophobicity without significantly disturbing the original features but also exhibits a novel catalytic activity in the Friedel-Crafts alkylation reaction of indoles with trans-ß-nitrostyrene because of the accessible sites and synergistic effects.
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BACKGROUND: The shortage of water resources and the increase of greenhouse gas emissions from soil seriously restrict the sustainable development of agriculture. Under the premise of ensuring a stable yield of winter wheat through a reasonable irrigation scenario, identifying a suitable straw returning method will have a positive effect on agricultural carbon sequestration and emission reduction in North China Plain. RESULTS: Straw burying (SR) and straw mulching (SM) were adopted based on traditional tillage under in the winter wheat growing season of 2020-2021 and 2021-2022. Three irrigation scenarios were used for each straw returning method: no irrigation (I0), irrigation 60 mm at jointing stage (I1), and irrigation of 60 mm each at the jointing and heading stages (I2). Soil moisture, soil respiration rate, cumulative soil CO2 emissions, yield, water use efficiency (WUE) and soil CO2 emission efficiency (CEE) were mainly studied. The results showed that, compared to SM, SR improved the utilization of soil water and enhanced soil carbon sequestration. SR reduced soil respiration rate and cumulative soil CO2 emissions in two winter wheat growing seasons, and increased yield by increasing spike numbers. In addition, with an increase in the amount of irrigation, soil CO2 emissions and yield increased. Under SR-I1 treatment, WUE and CEE were the highest. SR-I1 increases crop yields at the same time as reducing soil CO2 emissions. CONCLUSION: The combination of SR and irrigation 60 mm at jointing stage is a suitable straw returning irrigation scenario, which can improve water use and reduce soil CO2 emission in NCP. © 2023 Society of Chemical Industry.
Subject(s)
Soil , Triticum , Seasons , Carbon Dioxide/analysis , Water , Carbon , Agriculture/methods , ChinaABSTRACT
Object counting, defined as the task of accurately predicting the number of objects in static images or videos, has recently attracted considerable interest. However, the unavoidable presence of background noise prevents counting performance from advancing further. To address this issue, we created a group and graph attention network (GGANet) for dense object counting. GGANet is an encoder-decoder architecture incorporating a group channel attention (GCA) module and a learnable graph attention (LGA) module. The GCA module groups the feature map into several subfeatures, each of which is assigned an attention factor through the identical channel attention. The LGA module views the feature map as a graph structure in which the different channels represent diverse feature vertices, and the responses between channels represent edges. The GCA and LGA modules jointly avoid the interference of irrelevant pixels and suppress the background noise. Experiments are conducted on four crowd-counting datasets, two vehicle-counting datasets, one remote-sensing counting dataset, and one few-shot object-counting dataset. Comparative results prove that the proposed abbr achieves superior counting performance.
ABSTRACT
Tumor cell extravasation across endothelial barrier has been recognized as a pivotal event in orchestrating metastasis formation. This event is initiated by the interactions of extravasating tumor cells with endothelial cells (ECs). Therefore, targeting the crosstalk between tumor cells and ECs might be a promising therapeutic strategy to prevent metastasis. In this study, we demonstrated that Rh1, one of the main ingredients of ginseng, hindered the invasion of breast cancer (BC) cells as well as diminished the permeability of ECs both in vitro and in vivo, which was responsible for the attenuated tumor cell extravasation across endothelium. Noteworthily, we showed that ECs were capable of inducing the epithelial-mesenchymal transition (EMT) and invadopodia of BC cells that are essential for tumor cell migration and invasion through limiting the nuclear translocation of hematopoietically expressed homeobox (HHEX). The decreased nuclear HHEX paved the way for initiating the CCL20/CCR6 signaling axis, which in turn contributed to damaged endothelial junctions, uncovering a new crosstalk mode between tumor cells and ECs. Intriguingly, Rh1 inhibited the kinase activity of casein kinase II subunit alpha (CK2α) and further promoted the nuclear translocation of HHEX in the BC cells, which resulted in the disrupted crosstalk between chemokine (C-C motif) ligand 20 (CCL20) in the BC cells and chemokine (C-C motif) receptor 6 (CCR6) in the ECs. The prohibited CCL20-CCR6 axis by Rh1 enhanced vascular integrity and diminished tumor cell motility. Taken together, our data suggest that Rh1 serves as an effective natural CK2α inhibitor that can be further optimized to be a therapeutic agent for reducing tumor cell extravasation.
Subject(s)
Casein Kinase II , Genes, Homeobox , Endothelial Cells , Endothelium , ChemokinesABSTRACT
A general approach to prepare superhydrophobic MOFs (denoted as MOFs-CF3) through a post-decorating strategy for highly efficient chemical fixation of CO2 was demonstrated. The enhanced catalytic activity of MOFs-CF3 is attributed to a synergistic effect between the Lewis acid sites of MOFs and modification of the electron-withdrawing trifluoromethyl group, which resulted in a high CO2 enrichment capacity. The possible mechanism of cycloaddition catalyzed by the MOFs-CF3 catalyst was also proposed.
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The selectivity control of Pd nanoparticles (NPs) in the direct CO esterification with methyl nitrite toward dimethyl oxalate (DMO) or dimethyl carbonate (DMC) remains a grand challenge. Herein, Pd NPs are incorporated into isoreticular metal-organic frameworks (MOFs), namely UiO-66-X (X=-H, -NO2 , -NH2 ), affording Pd@UiO-66-X, which unexpectedly exhibit high selectivity (up to 99 %) to DMC and regulated activity in the direct CO esterification. In sharp contrast, the Pd NPs supported on the MOF, yielding Pd/UiO-66, displays high selectivity (89 %) to DMO as always reported with Pd NPs. Both experimental and DFT calculation results prove that the Pd location relative to UiO-66 gives rise to discriminated microenvironment of different amounts of interface between Zr-oxo clusters and Pd NPs in Pd@UiO-66 and Pd/UiO-66, resulting in their distinctly different selectivity. This is an unprecedented finding on the production of DMC by Pd NPs, which was previously achieved by Pd(II) only, in the direct CO esterification.
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Inspiration from natural enzymes enabling creationary catalyst design is appealing yet remains extremely challenging for selective methane (CH4) oxidation. This study presents the construction of a biomimetic catalyst platform for CH4 oxidation, which is constructed by incorporating Fe-porphyrin into a robust metal-organic framework, UiO-66, furnished with saturated monocarboxylic fatty acid bearing different long alkyl chains. The catalysts demonstrate the high efficiency in the CH4 to methanol (CH3OH) conversion at 50 °C. Moreover, the selectivity to CH3OH can be effectively regulated and promoted through a fine-tuned microenvironment by hydrophobic modification around the Fe-porphyrin. The long-chain fatty acids anchored on the Zr-oxo cluster of UiO-66 can not only tune the electronic state of the Fe sites to improve CH4 adsorption, but also restrict the amount of H2O2 around the Fe sites to reduce the overoxidation. This behavior resembles the microenvironment regulation in methane monooxygenase, resulting in high CH3OH selectivity.
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Human behavior recognition technology is widely adopted in intelligent surveillance, human-machine interaction, video retrieval, and ambient intelligence applications. To achieve efficient and accurate human behavior recognition, a unique approach based on the hierarchical patches descriptor (HPD) and approximate locality-constrained linear coding (ALLC) algorithm is proposed. The HPD is a detailed local feature description, and ALLC is a fast coding method, which makes it more computationally efficient than some competitive feature-coding methods. Firstly, energy image species were calculated to describe human behavior in a global manner. Secondly, an HPD was constructed to describe human behaviors in detail through the spatial pyramid matching method. Finally, ALLC was employed to encode the patches of each level, and a feature coding with good structural characteristics and local sparsity smoothness was obtained for recognition. The recognition experimental results on both Weizmann and DHA datasets demonstrated that the accuracy of five energy image species combined with HPD and ALLC was relatively high, scoring 100% in motion history image (MHI), 98.77% in motion energy image (MEI), 93.28% in average motion energy image (AMEI), 94.68% in enhanced motion energy image (EMEI), and 95.62% in motion entropy image (MEnI).
Subject(s)
Algorithms , Pattern Recognition, Automated , Humans , Pattern Recognition, Automated/methodsABSTRACT
The chemical microenvironment modulation of metal nanoparticles (NPs) holds promise for tackling the long-lasting challenge of the trade-off effect between activity and selectivity in catalysis. Herein, ultrafine PdCu2 NPs incorporated into covalent organic frameworks (COFs) with diverse groups on their pore walls have been fabricated for the semihydrogenation of alkynes. The Cu species, as the primary microenvironment of Pd active sites, greatly improves the selectivity. The functional groups as the secondary microenvironment around PdCu2 NPs effectively regulate the activity, in which PdCu2 NPs encapsulated in the COF bearing -CH3 groups exhibit the highest activity with >99 % conversion and 97 % selectivity. Both experimental and calculation results suggest that the functional group affects the electron-donating ability of the COFs, which successively impacts the charge transfer between COFs and Pd sites, giving rise to a modulated Pd electronic state and excellent catalytic performance.
Subject(s)
Metal Nanoparticles , Metal-Organic Frameworks , Alkynes , Catalysis , ElectronicsABSTRACT
ETHNOPHARMACOLOGICAL RELEVANCE: Shixiao San (SXS) is a traditional Chinese formula that has been widely used in clinical practice to treat blood stasis syndromes, such as hyperlipidemia, atherosclerotic, thrombosis and coronary heart disease. However, the effectiveness and mechanism of SXS have not been studied in detail yet. AIM OF THE STUDY: Current study aimed to identify the compounds in SXS, evaluate the formula efficacies using network pharmacology, molecular docking, and verify the pharmacological effects by in vivo and in vitro experiments. MATERIALS AND METHODS: The compounds in SXS were analyzed using UPLC-QTOF-MS. Potential target genes for identified compounds were obtained from three databases. DAVID database was used to perform GO and KEGG pathway enrichment analyses. PPI network was constructed to screen core targets. Molecular docking was used to examine interactions between active compounds and potential targets. The mechanism was also verified by model of acute blood stasis rats and human umbilical vein cells. RESULTS: In total, 45 compounds were identified from SXS. Among the detected phytochemicals, quercetin, isorhamnetin, kaempferol, D-catechin, naringenin and amentoflavone were identified as the active constituents. SXS is primarily involved in the modulation of hypoxic state, vascular regulation, and inflammation response, according to GO and KGG pathway enrichment analysis. A network of protein-protein interactions (PPIs) was constructed and five core targets were identified as VEGFA, AKT1, EGFR, PTGS2, and MMP9. Molecular docking simulation revealed good binding affinity of the five putative targets with the corresponding compounds. SXS reduced HIF-1α and COX-2 levels and increased the eNOS expression levels in hypoxic HUVECs. SXS can reduce the whole blood viscosity in adrenaline induced acute blood stasis rats and relieve blood stasis. CONCLUSIONS: SXS removes blood stasis might through VEGFA/AKT/eNOS/COX-2 pathway and flavonoids are the main active components in the formula.
Subject(s)
Drugs, Chinese Herbal , Humans , Rats , Animals , Molecular Docking Simulation , Drugs, Chinese Herbal/pharmacology , Drugs, Chinese Herbal/therapeutic use , Drugs, Chinese Herbal/chemistry , Cyclooxygenase 2 , Network PharmacologyABSTRACT
Four fractions of polysaccharides (TPP-1, TPP-2, TPP-3, and TPP-4) were isolated and purified from the pollen of Typha angustifolia L., and the structure of TPP-3 was furtherly determined by HPGPC (High Performance Gel Permeation Chromatography), monosaccharide composition analysis, methylation analysis and NMR (Nuclear Magnetic Resonance). TPP-3 was found to be a homogeneous heteropolysaccharide with an average molecular weight of 5.5 × 104 Da and composed of eight types of monosaccharides. The pro-angiogenic activities of TPP-3 were verified on HUVECs and VEGFR tyrosine kinase inhibitor II (VRI)-induced vascular defect zebrafish model. Furthermore, the underlying mechanism investigation showed that its pro-angiogenic activities were closely related with the activation of VEGF/PI3K/Akt signaling pathway.
Subject(s)
Typhaceae , Zebrafish , Animals , Zebrafish/metabolism , Phosphatidylinositol 3-Kinases/metabolism , Angiogenesis Inducing Agents/pharmacology , Polysaccharides/chemistry , Monosaccharides/analysis , Pollen/chemistryABSTRACT
The exposed facets of supported catalysts play a crucial role in catalysis; however, they are usually ignored and related studies remain rare. Herein, we have fabricated a series of sandwich-structured metal-organic framework composites, denoted ZIF-8X @Pd@ZIF-8 (x represents the morphology of ZIF-8 core, i.e., ZIF-8C exposing (100) facet, ZIF-8RD exposing (110) facet, and ZIF-8TRD exposing mixed (100) and (110) facets), featuring Pd nanoparticles deposited on the specific crystal facets of ZIF-8 core, for hydrogenation of p-chloronitrobenzene. The Pd electronic state is tailored by the ZIF-8 core, where more electron-deficient Pd is found in ZIF-8C @Pd@ZIF-8 than that in ZIF-8RD @Pd@ZIF-8, leading to discriminative adsorption of the -NO2 and -Cl groups of p-chloronitrobenzene. Consequently, ZIF-8C @Pd@ZIF-8 exhibits excellent activity (97.6 %) and selectivity (98.1 %) to p-chloroaniline. This work highlights crystal facet engineering of supports to modulate the microenvironment and electronic state of supported metal nanoparticles, offering a promising avenue to enhanced catalysis.
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Counting the number of people in crowded scenarios is a crucial task in video surveillance and urban security system. Widely deployed surveillance cameras provide big data for training, a compelling deep learning-based counting network. However, large-scale variations in dense crowds are still not entirely solved. To address this problem, we propose a spatial-frequency attention network (SFANet) for crowd counting in this article. A bottleneck spatial attention module is built to emphasize features in various spatial locations and select a region containing individuals adaptively in the spatial domain. As a complementary, in the frequency domain, a multispectral channel attention module is adopted to obtain a more complete set of frequency components for representing each channel. The two attention modules are combined to focus on the discriminative region and suppress the misleading information by their mutual promotion. Experimental results on five benchmark crowd data sets demonstrate that the SFANet can achieve the state-of-the-art performance in terms of accuracy and robustness.
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Charge transfer between metal sites and supports is crucial for catalysis. Redox-inert supports are usually unfavorable due to their less electronic interaction with metal sites, which, we demonstrate, is not always correct. Herein, three metal-organic frameworks (MOFs) are chosen to mimic inert or active supports for Pt nanoparticles (NPs) and the photocatalysis is studied. Results demonstrate the formation of a Schottky junction between Pt and the MOFs, leading to the electron-donation effect of the MOFs. Under light irradiation, both the MOF electron-donation effect and Pt interband excitation dominate the Pt electron density. Compared with the "active" UiO-66 and MIL-125 supports, Pt NPs on the "inert" ZIF-8 exhibit higher electron density due to the higher Schottky barrier, resulting in superior photocatalytic activity. This work optimizes metal catalysts with non-reducible supports, and promotes the understanding of the relationship between the metal-support interaction and photocatalysis.
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BACKGROUND: Carbonized traditional Chinese medicine (TCM) is a kind of distinctive traditional medicine, which has been widely used to cure various bleeding syndromes in clinic for over 2000 years. However, there are no effective quality control methods developed on carbonized TCM so far. PURPOSE: This study aimed at developing a processing-associated quality marker (Q-marker) discovery strategy, which would enable to promote the quality control study of carbonized TCM. METHODS: Carbonized Typhae Pollen (CTP), a typical carbonized TCM with fantastic efficacy of stanching bleeding and removing blood stasis, was used as an example. First, a ultraperformance liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) method was established to characterize four types of CTP in different processing degrees. Second, chemometric method was applied to screen candidate Q-markers. Third, peak area changes and Aratio changes of each candidate markers in 57 batches samples were described (Traceability and Transitivity). Fourth, systems pharmacology and two high-throughput zebrafish models: cerebral hemorrhage model and thrombus model were used to furtherly screen Q-markers (Effectiveness). Finally, a ultraperformance liquid chromatographic coupled with triple quadrupole tandem mass spectrometry (UPLC-TQ-MS) method was established and applied to quantify Q-markers in additional 10 batches of CTP samples (Measurability). RESULTS: The chemical profiles of Typhae Pollen during the carbonized process were investigated. Then, 12 candidate compounds were screened in chemometric part. Six Q-markers (isorhamnetin-3-O-neohesperidoside, isorhamnetin-3-O-rutinoside, kaempferol-3-O-neohesperidoside, naringenin, quercetin and isorhamnetin) were subsequently screened out using three principles of Q-markers combined with content changes and two in vivo zebrafish models. Their average contents in additional 10 batches of CTP were 316.8 µg/g, 13.7 µg/g, 6.1 µg/g, 197.8 µg/g, 12.9 µg/g and 199.3 µg/g, respectively. Their content proportion was about 25: 1: 0.5: 15: 1: 15. CONCLUSION: A processing-associated Q-marker discovery strategy was developed for carbonized TCM. It might provide a novel insight to solve the problem of 'Chao Tan Cun Xing' in carbonized process.
Subject(s)
Drugs, Chinese Herbal , Medicine, Chinese Traditional , Animals , Biomarkers/analysis , Chromatography, High Pressure Liquid/methods , Drugs, Chinese Herbal/chemistry , High-Throughput Screening Assays , Metabolomics/methods , Network Pharmacology , Tandem Mass Spectrometry/methods , ZebrafishABSTRACT
In this research, an image defogging algorithm is proposed for the electricity transmission line monitoring system in the smart city. The electricity transmission line image is typically situated in the top part of the image which is rather thin in size. Because the electricity transmission line is situated outside, there is frequently a sizable amount of sky in the backdrop. Firstly, an optimized quadtree segmentation method for calculating global atmospheric light is proposed, which gives higher weight to the upper part of the image with the sky region. This prevents interference from bright objects on the ground and guarantees that the global atmospheric light is computed in the top section of the image with the sky region. Secondly, a method of transmission calculation based on dark pixels is introduced. Finally, a detail sharpening post-processing based on visibility level and air light level is introduced to enhance the detail level of electricity transmission lines in the defogging image. Experimental results indicate that the algorithm performs well in enhancing the image details, preventing image distortion and avoiding image oversaturation.