Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 1.059
Filtrar
1.
Sci Total Environ ; 855: 158876, 2023 Jan 10.
Artigo em Inglês | MEDLINE | ID: mdl-36152866

RESUMO

Biochar aging affects the stability of soil carbon. Analyzing the effect of biochar on soil organic carbon (SOC) forms and their relations with microbial community assembly and carbon metabolism with time is helpful for soil carbon sequestration (by adapting the farm management approach). Four treatments with no, low, medium, and high biochar application rates (0 %, 1 %, 2 %, and 4 % of the total dry weight of topsoil before winter wheat planting, abbreviated as control, LB, MB, and HB, respectively) were conducted in the field. The SOC and particulate organic carbon positively correlated with the biochar application rate. Biochar decreased readily oxidizable carbon (P < 0.05) after 8 months of application compared to the control; however, the difference disappeared with time. Biochar increased dissolved organic carbon (DOC) but had no effect on water- soluble organic carbon (WSOC); DOC and WSOC decreased with time. Furthermore, LB and HB stabilized the bacterial alpha diversities with time. Based on high-throughput sequencing, HB reduced the relative abundance of Actinobacteriota but increased that of Acidobacteria (P < 0.05) after 12 months of biochar application. Time-wise, the bacterial community assembly was determined by deterministic processes that were significantly affected by the available nitrogen, DOC, or WSOC. Compared with the control, biochar decreased bacterial links and improved bacterial metabolism of phenolic acids and polymers with time, as evidenced by Biolog EcoPlates. Structural equation modeling revealed that the contribution of bacterial assembly processes to carbon metabolism changed with time. Microbial carbon metabolism was most positively influenced by differences in the composition of bacterial specialists. These findings reinforced that changes in soil labile organic carbon were time-dependent but not necessarilty affected by the biochar application rate.


Assuntos
Carbono , Solo , Solo/química , Carvão Vegetal/química , Sequestro de Carbono , Microbiologia do Solo , Bactérias , Água
2.
Sensors (Basel) ; 22(21)2022 Oct 29.
Artigo em Inglês | MEDLINE | ID: mdl-36366000

RESUMO

As one of the pioneering data representations, the point cloud has shown its straightforward capacity to depict fine geometry in many applications, including computer graphics, molecular structurology, modern sensing signal processing, and more. However, unlike computer graphs obtained with auxiliary regularization techniques or from syntheses, raw sensor/scanner (metric) data often contain natural random noise caused by multiple extrinsic factors, especially in the case of high-speed imaging scenarios. On the other hand, grid-like imaging techniques (e.g., RGB images or video frames) tend to entangle interesting aspects with environmental variations such as pose/illuminations with Euclidean sampling/processing pipelines. As one such typical problem, 3D Facial Expression Recognition (3D FER) has been developed into a new stage, with remaining difficulties involving the implementation of efficient feature abstraction methods for high dimensional observations and of stabilizing methods to obtain adequate robustness in cases of random exterior variations. In this paper, a localized and smoothed overlapping kernel is proposed to extract discriminative inherent geometric features. By association between the induced deformation stability and certain types of exterior perturbations through manifold scattering transform, we provide a novel framework that directly consumes point cloud coordinates for FER while requiring no predefined meshes or other features/signals. As a result, our compact framework achieves 78.33% accuracy on the Bosphorus dataset for expression recognition challenge and 77.55% on 3D-BUFE.


Assuntos
Reconhecimento Facial , Imageamento Tridimensional/métodos
3.
Front Oncol ; 12: 950418, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36387243

RESUMO

Background: Peritoneal sarcomatosis (PS) could occur in patients with retroperitoneal sarcomas (RPS). This study aimed to expand the understanding of PS on its characteristics and prognostic role, and develop a nomogram to predict its occurrence preoperatively. Methods: Data of 211 consecutive patients with RPS who underwent surgical treatment between 2011 and 2019 was retrospectively reviewed. First, the clinicopathological characteristics of PS were summarized and analyzed. Second, the disease-specific survival (DSS) and recurrence-free survival (RFS) of patients were analyzed to evaluate the prognostic role of PS. Third, preoperative imaging, nearly the only way to detect PS preoperatively, was combined with other screened risk factors to develop a nomogram. The performance of the nomogram was assessed. Results: Among the 211 patients, 49 (23.2%) patients had PS with an incidence of 13.0% in the primary patients and 35.4% in the recurrent patients. The highest incidence of PS occurred in dedifferentiated liposarcoma (25.3%) and undifferentiated pleomorphic sarcoma (25.0%). The diagnostic sensitivity of the preoperative imaging was 71.4% and its specificity was 92.6%. The maximum standardized uptake value (SUVmax) was elevated in patients with PS (P<0.001). IHC staining for liposarcoma revealed that the expression of VEGFR-2 was significantly higher in the PS group than that in the non-PS group (P = 0.008). Survival analysis (n =196) showed significantly worse DSS in the PS group than in non-PS group (median: 16.0 months vs. not reached, P < 0.001). In addition, PS was proven as one of the most significant prognostic predictors of both DSS and RFS by random survival forest algorithm. A nomogram to predict PS status was developed based on preoperative imaging combined with four risk factors including the presentation status (primary vs. recurrent), ascites, SUVmax, and tumor size. The nomogram significantly improved the diagnostic sensitivity compared to preoperative imaging alone (44/49, 89.8% vs. 35/49, 71.4%). The C-statistics of the nomogram was 0.932, and similar C-statistics (0.886) was achieved at internal cross-validation. Conclusion: PS is a significant prognostic indicator for RPS, and it occurs more often in recurrent RPS and in RPS with higher malignant tendency. The proposed nomogram is effective to predict PS preoperatively.

4.
Artigo em Inglês | MEDLINE | ID: mdl-36409291

RESUMO

Regarding the global energy crisis, it is of profound significance to develop spontaneous power generators that harvest natural energy. Fabricating humidity-responsive actuators that can conduct such energy transduction is of paramount importance. Herein, we incorporate covalent organic frameworks with flexible polyethylene glycol to fabricate rigid-flexible coupled membrane actuators. This strategy significantly improves the mechanical properties and humidity-responsive performance of the actuators, meanwhile the existence of ordered structures enables us to unveil the actuation mechanism. These high-performance actuators can achieve various actuation applications and exhibit interesting self-oscillation behavior above a water surface. Finally, after being coupled with a piezoelectric film, the bilayer device can spontaneously output electricity over 2 days. This work paves a new avenue to fabricate rigid-flexible coupled actuators for self-sustained energy transduction.

5.
Phys Med Biol ; 67(22)2022 Nov 18.
Artigo em Inglês | MEDLINE | ID: mdl-36401576

RESUMO

Objective.Effective learning and modelling of spatial and semantic relations between image regions in various ranges are critical yet challenging in image segmentation tasks.Approach.We propose a novel deep graph reasoning model to learn from multi-order neighborhood topologies for volumetric image segmentation. A graph is first constructed with nodes representing image regions and graph topology to derive spatial dependencies and semantic connections across image regions. We propose a new node attribute embedding mechanism to formulate topological attributes for each image region node by performing multi-order random walks (RW) on the graph and updating neighboring topologies at different neighborhood ranges. Afterwards, multi-scale graph convolutional autoencoders are developed to extract deep multi-scale topological representations of nodes and propagate learnt knowledge along graph edges during the convolutional and optimization process. We also propose a scale-level attention module to learn the adaptive weights of topological representations at multiple scales for enhanced fusion. Finally, the enhanced topological representation and knowledge from graph reasoning are integrated with content features before feeding into the segmentation decoder.Main results.The evaluation results over public kidney and tumor CT segmentation dataset show that our model outperforms other state-of-the-art segmentation methods. Ablation studies and experiments using different convolutional neural networks backbones show the contributions of major technical innovations and generalization ability.Significance.We propose for the first time an RW-driven MCG with scale-level attention to extract semantic connections and spatial dependencies between a diverse range of regions for accurate kidney and tumor segmentation in CT volumes.


Assuntos
Aprendizado Profundo , Neoplasias , Humanos , Algoritmos , Redes Neurais de Computação , Rim
6.
iScience ; 25(11): 105329, 2022 Nov 18.
Artigo em Inglês | MEDLINE | ID: mdl-36325060

RESUMO

Glioblastoma (GBM) is identified to share common signal pathways between glioma and immune cells. Here, we find that T cell immunoglobulin domain and mucin domain protein 3 (TIM-3) is one of the most common co-inhibitory immune checkpoints in GBM shared by tumor and non-tumor cells. Glioma cell-intrinsic TIM-3 is involved in not only regulating malignant behaviors of glioma cells but also inducing macrophage migration and transition to anti-inflammatory/pro-tumorigenic phenotype by a TIM-3/interleukin 6 (IL6) signal. In mechanism, as one of the major regulators of IL6, TIM-3 regulates its expression through activating NF-κB. Blocking this feedback loop by Tocilizumab, an IL6R inhibitor, inhibited the above effects and repressed the tumorigenicity of GBM in vivo. Our work identifies glioma cell-intrinsic functions of TIM-3/IL6 signal mediating the crosstalk feedback loop between glioma cells and tumor-associated macrophages (TAMs). Blocking this feedback loop may provide a novel therapeutic strategy for GBM.

7.
Adv Sci (Weinh) ; : e2203683, 2022 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-36319474

RESUMO

Metal halide perovskites have drawn substantial interest in optoelectronic devices in the past decade. Perovskite/electrode contacts are crucial for constructing high-performance charge-transporting-layer-free perovskite devices, such as solar cells, field-effect transistors, artificial synapses, memories, etc. Many studies have evidenced that the perovskite layer can directly contact the electrodes, showing abundant physicochemical, electronic, and photoelectric properties in charge-transporting-layer-free perovskite devices. Meanwhile, for perovskite/metal contacts, some critical interfacial physical and chemical processes are reported, including band bending, interface dipoles, metal halogenation, and perovskite decomposition induced by metal electrodes. Thus, a systematic summary of the role of metal halide perovskite/electrode contacts on device performance is essential. This review summarizes and discusses charge carrier dynamics, electronic band engineering, electrode corrosion, electrochemical metallization and dissolution, perovskite decomposition, and interface engineering in perovskite/electrode contacts-based electronic devices for a comprehensive understanding of the contacts. The physicochemical, electronic, and morphological properties of various perovskite/electrode contacts, as well as relevant engineering techniques, are presented. Finally, the current challenges are analyzed, and appropriate recommendations are put forward. It can be expected that further research will lead to significant breakthroughs in their application and promote reforms and innovations in future solid-state physics and materials science.

8.
PLoS One ; 17(11): e0274968, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36350806

RESUMO

Immersive projection display system is widely adopted in virtual reality and various exhibition halls. How to maintain high display quality in an immersive projection environment with uneven illumination and the color deviation caused by the inter-reflection of light is still a challenging task. In this paper, we innovatively propose a deep learning-based radiation compensation for an L-shaped projector-camera system. This method employs complex reflection phenomena to simulate the light transport processing in an L-shaped environment, we also designed a Dark-Channel Enhanced-Compensation Net (DECNet) which composed of a convolutional neural network called Compensation Net, a DarkChannelNet and another subnet (such as sensing network) aiming at achieving high-quality reproduction of projected display images. The final output of DECNet is the compensation image to be projected. It is always a critical problem to establish appropriate evaluation and analysis indexes throughout the research of light pollution compensation algorithms. In this paper, PSNR, SSIM, and RMSE are proposed to quantitatively analyze the image quality. The experimental results show that this method has certain advantages in reducing the inter-reflection of the projection plane. And our method could also well replace the traditional process using the backlight transmission matrix. It can be concluded to a certain that this method can be extended to other more complex projection environments with strong scalability and inclusiveness.


Assuntos
Algoritmos , Redes Neurais de Computação , Processamento de Imagem Assistida por Computador/métodos
9.
Nat Commun ; 13(1): 7000, 2022 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-36385244

RESUMO

The Su-Schrieffer-Heeger (SSH) model in a two-dimensional rectangular lattice features gapless or gapped Dirac cones with topological edge states along specific peripheries. While such a simple model has been recently realized in photonic/acoustic lattices and electric circuits, its material realization in condensed matter systems is still lacking. Here, we study the atomic and electronic structure of a rectangular Si lattice on Ag(001) by angle-resolved photoemission spectroscopy and theoretical calculations. We demonstrate that the Si lattice hosts gapped Dirac cones at the Brillouin zone corners. Our tight-binding analysis reveals that the Dirac bands can be described by a 2D SSH model with anisotropic polarizations. The gap of the Dirac cone is driven by alternative hopping amplitudes in one direction and staggered potential energies in the other one and hosts topological edge states. Our results establish an ideal platform to explore the rich physical properties of the 2D SSH model.

10.
Front Neurol ; 13: 1013062, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36388174

RESUMO

Objective: Nuclear factor erythroid 2-related factor 2 (Nrf2) may harbor endogenous neuroprotective role. We strived to ascertain the prognostic significance of serum Nrf2 in severe traumatic brain injury (sTBI). Methods: This prospective cohort study included 105 controls and 105 sTBI patients, whose serum Nrf2 levels were quantified. Its relations to traumatic severity and 180-day overall survival, mortality, and poor prognosis (extended Glasgow Outcome Scale score 1-4) were discerned using multivariate analysis. Results: There was a substantial enhancement of serum Nrf1 levels of patients (median, 10.9 vs. 3.3 ng/ml; P < 0.001), as compared to controls. Serum Nrf2 levels were independently correlative to Rotterdam computed tomography (CT) scores (ρ = 0.549, P < 0.001; t = 2.671, P = 0.009) and Glasgow Coma Scale (GCS) scores (ρ = -0.625, P < 0.001; t = -3.821, P < 0.001). Serum Nrf2 levels were significantly higher in non-survivors than in survivors (median, 12.9 vs. 10.3 ng/ml; P < 0.001) and in poor prognosis patients than in good prognosis patients (median, 12.5 vs. 9.4 ng/ml; P < 0.001). Patients with serum Nrf2 levels > median value (10.9 ng/ml) had markedly shorter 180-day overall survival time than the other remainders (mean, 129.3 vs. 161.3 days; P = 0.002). Serum Nrf2 levels were independently predictive of 180-day mortality (odds ratio, 1.361; P = 0.024), overall survival (hazard ratio, 1.214; P = 0.013), and poor prognosis (odds ratio, 1.329; P = 0.023). Serum Nrf2 levels distinguished the risks of 180-day mortality and poor prognosis with areas under receiver operating characteristic curve (AUCs) at 0.768 and 0.793, respectively. Serum Nrf2 levels > 10.3 ng/ml and 10.8 ng/ml discriminated patients at risk of 180-day mortality and poor prognosis with the maximum Youden indices of 0.404 and 0.455, respectively. Serum Nrf2 levels combined with GCS scores and Rotterdam CT scores for death prediction (AUC, 0.897; 95% CI, 0.837-0.957) had significantly higher AUC than GCS scores (P = 0.028), Rotterdam CT scores (P = 0.007), or serum Nrf2 levels (P = 0.006) alone, and the combination for poor outcome prediction (AUC, 0.889; 95% CI, 0.831-0.948) displayed significantly higher AUC than GCS scores (P = 0.035), Rotterdam CT scores (P = 0.006), or serum Nrf2 levels (P = 0.008) alone. Conclusion: Increased serum Nrf2 levels are tightly associated with traumatic severity and prognosis, supporting the considerable prognostic role of serum Nrf2 in sTBI.

11.
Entropy (Basel) ; 24(11)2022 Nov 13.
Artigo em Inglês | MEDLINE | ID: mdl-36421501

RESUMO

Data representation has been one of the core topics in 3D graphics and pattern recognition in high-dimensional data. Although the high-resolution geometrical information of a physical object can be well preserved in the form of metrical data, e.g., point clouds/triangular meshes, from a regular data (e.g., image/audio) processing perspective, they also bring excessive noise in the course of feature abstraction and regression. For 3D face recognition, preceding attempts focus on treating the scan samples as signals laying on an underlying discrete surface (mesh) or morphable (statistic) models and by embedding auxiliary information, e.g., texture onto the regularized local planar structure to obtain a superior expressive performance to registration-based methods, but environmental variations such as posture/illumination will dissatisfy the integrity or uniform sampling condition, which holistic models generally rely on. In this paper, a geometric deep learning framework for face recognition is proposed, which merely requires the consumption of raw spatial coordinates. The non-uniformity and non-grid geometric transformations in the course of point cloud face scanning are mitigated by modeling each identity as a stochastic process. Individual face scans are considered realizations, yielding underlying inherent distributions under the appropriate assumption of ergodicity. To accomplish 3D facial recognition, we propose a windowed solid harmonic scattering transform on point cloud face scans to extract the invariant coefficients so that unrelated variations can be encoded into certain components of the scattering domain. With these constructions, a sparse learning network as the semi-supervised classification backbone network can work on reducing intraclass variability. Our framework obtained superior performance to current competing methods; without excluding any fragmentary or severely deformed samples, the rank-1 recognition rate (RR1) achieved was 99.84% on the Face Recognition Grand Challenge (FRGC) v2.0 dataset and 99.90% on the Bosphorus dataset.

12.
Artigo em Inglês | MEDLINE | ID: mdl-36350447

RESUMO

With the growth of global food demand, agricultural carbon emissions caused by agricultural production have become a major challenge in controlling global warming. However, a systematic and visual literature review of food security and carbon emissions (FSCE) is still lacking, and there is a lack of exploration on the balanced path between ensuring food security and realizing carbon emission reduction. Based on 872 articles related to FSCE in the Web of Science (WOS) core database, this paper used CiteSpace and VOSviewer bibliometric software to analyze the relevant research focus and trends. This study found that developed countries dominated the research in this field, and the quantity, quality, and intensity of their authors, institutions, and cooperation among countries are higher than those of developing countries. Although the intensity of interdisciplinary cooperation has increased, it remains at a low level. Since 2007, the number of papers published in this field has increased significantly, and the research perspectives have diversified. Moreover, the research theme continues to expand with the core of "food security," involving the impact of climate change, crop production and food security, soil carbon sequestration, and farmers' livelihood sustainability. In addition, food production, food transportation, and food loss reduction are key paths that need to be balanced to ensure global food security and realize carbon emission reduction, and how to promote "economic growth" under the constraints of FSCE will be a future research hotspot.

13.
STAR Protoc ; 3(4): 101792, 2022 12 16.
Artigo em Inglês | MEDLINE | ID: mdl-36317173

RESUMO

The morphology of nano-Cu2O profoundly determines its catalytic performance. Here, we provide two universal and reliable techniques to modify the surface of nano-Cu2O. First, we detail steps for the systematic tuning of the exposed facets of nano-Cu2O ranging from low index to high index using reductant-controlled technique in the presence of sodium dodecyl sulfate. Second, we describe steps for facet-directed precipitation in which the morphology-dependent ZIF-8 (a type of zeolitic imidazolate frameworks) shells on different nano-Cu2O are well introduced. For complete details on the use and execution of this protocol, please refer to Luo et al. (2022).


Assuntos
Zeolitas , Catálise
14.
J Environ Manage ; 326(Pt B): 116790, 2022 Nov 15.
Artigo em Inglês | MEDLINE | ID: mdl-36399809

RESUMO

Biochar that is directly obtained by pyrolysis exhibits a low adsorption efficiency; furthermore, the process of recycling adsorbents is ineffective. To solve these problems, conventional chemical coprecipitation, sol-gel, multimetal multilayer loading and biomass pyrolysis coking processes have been integrated. After selecting specific components for structural design, a novel high-performance biochar adsorbent was obtained. The effects of the O2 concentration and temperature on the regeneration characteristics were explored. An isothermal regeneration method to repair the deactivated adsorbent in a specific atmosphere was proposed, and the optimal regeneration mode and conditions were determined. The microscopic characteristics of the regenerated samples were revealed along with the mechanism of Hg0 removal and regeneration by using temperature-programmed desorption technology and adsorption kinetics. The results show that doping multiple metals can reduce the pyrolysis reaction barrier of the modified biomass. On the modified surface of the sample, the doped metals formed aggregated oxides, and the resulting synergistic effect enhanced the oxidative activity of the biochar carriers and the threshold effect of Ce oxide. The optimal regeneration conditions (5% O2 and 600 °C) effectively coordinated the competitive relationship between the deep carbonization process and the adsorption/oxidation site repair process; in addition, these conditions provided outstanding structure-effect connections between the physico-chemical properties and Hg0 removal efficiency of the regenerated samples. Hg0 adsorption by the regenerated samples is a multilayer mass transfer process that involves the coupling of physical and chemical effects, and the surface adsorption sites play a leading role.

15.
Front Cell Infect Microbiol ; 12: 1047306, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36405961

RESUMO

Background: Our previous study developed a novel peptide-based vaccine, MP3RT, to fight against tuberculosis (TB) infection in a mouse model. However, the consistency between the immunoinformatics predictions and the results of real-world animal experiments on the MP3RT vaccine remains unclear. Method: In this study, we predicted the antigenicity, immunogenicity, physicochemical parameters, secondary structure, and tertiary structure of MP3RT using bioinformatics technologies. The immune response properties of the MP3RT vaccine were then predicted using the C-ImmSim server. Finally, humanized mice were used to verify the characteristics of the humoral and cellular immune responses induced by the MP3RT vaccine. Results: MP3RT is a non-toxic and non-allergenic vaccine with an antigenicity index of 0.88 and an immunogenicity index of 0.61, respectively. Our results showed that the MP3RT vaccine contained 53.36% α-helix in the secondary structure, and the favored region accounted for 98.22% in the optimized tertiary structure. The binding affinities of the MP3RT vaccine to the human leukocyte antigen (HLA)-DRB1*01:01 allele, toll-like receptor-2 (TLR-2), and TLR-4 receptors were -1234.1 kcal/mol, -1066.4 kcal/mol, and -1250.4 kcal/mol, respectively. The results of the C-ImmSim server showed that the MP3RT vaccine could stimulate T and B cells to produce immune responses, such as high levels of IgM and IgG antibodies, IFN-γ, TNF-α, and IL-2 cytokines. Results from real-world animal experiments showed that the MP3RT vaccine could stimulate the humanized mice to produce high levels of IgG and IgG2a antibodies and IFN-γ+ T lymphocytes. Furthermore, the levels of IFN-γ, IL-2, and IL-6 cytokines in mice immunized with the MP3RT vaccine were significantly higher than those in the control group. Conclusion: MP3RT is a highly antigenic and immunogenic potential vaccine that can effectively induce Th1-type immune responses in silico analysis and animal experiments. This study lays the foundation for evaluating the value of computational tools and immunoinformatic techniques in reverse vaccinology research.


Assuntos
Experimentação Animal , Vacinas contra a Tuberculose , Tuberculose , Humanos , Camundongos , Animais , Interleucina-2 , Vacinas de Subunidades , Citocinas , Imunoglobulina G , Tuberculose/prevenção & controle
16.
BMC Genomics ; 23(1): 773, 2022 Nov 25.
Artigo em Inglês | MEDLINE | ID: mdl-36434504

RESUMO

BACKGROUND: Squamous promoter binding protein-like (SPL) proteins are a class of transcription factors that play essential roles in plant growth and development, signal transduction, and responses to biotic and abiotic stresses. The rapid development of whole genome sequencing has enabled the identification and characterization of SPL gene families in many plant species, but to date this has not been performed in quinoa (Chenopodium quinoa). RESULTS: This study identified 23 SPL genes in quinoa, which were unevenly distributed on 18 quinoa chromosomes. Quinoa SPL genes were then classified into eight subfamilies based on homology to Arabidopsis thaliana SPL genes. We selected three dicotyledonous and monocotyledonous representative species, each associated with C. quinoa, for comparative sympatric mapping to better understand the evolution of the developmental mechanisms of the CqSPL family. Furthermore, we also used 15 representative genes from eight subfamilies to characterize CqSPLs gene expression in different tissues and at different fruit developmental stages under six different abiotic stress conditions. CONCLUSIONS: This study, the first to identify and characterize SPL genes in quinoa, reported that CqSPL genes, especially CqSPL1, play a critical role in quinoa development and in its response to various abiotic stresses.

17.
J Hazard Mater ; 445: 130442, 2022 Nov 22.
Artigo em Inglês | MEDLINE | ID: mdl-36436454

RESUMO

It has been considered challenging to develop ideal adsorbents for efficient and lower adsorption time uranium extraction, especially 3D covalent organic frameworks with interpenetrating topologies and tunable porous structures. Here, a "soft" three-dimensional (3D) covalent organic framework (TAM-DHBD) with a fivefold interpenetrating structure is prepared as a novel porous platform for the efficient extraction of radioactive uranium. The resultant TAM-DHBD appears exceptional crystallinity, prominent porosity and excellent chemical stability. Based on the strong mutual coordination between phenolic-hydroxyl/imine-N on the main chain and uranium, TAM-DHBD can effectively avert the competition of other ions, showing high selectivity for uranium extraction. Impressively, the 3D ultra-hydrophilic transport channels and multi-directional uniform pore structure of TAM-DHBD lay the foundation for the ultra-high-speed diffusion of uranium (the adsorption equilibrium can be reached within 60 min under a high-concentration environment). Furthermore, the utilization of lightweight structure not only increases the adsorption site density, but renders the adsorption process flexible, achieving a breakthrough adsorption capacity of 1263.8 mg g-1. This work not only highlights new opportunities for designing microporous 3D COFs, but paves the way for the practical application of 3D COFs for uranium adsorption.

18.
J Agric Food Chem ; 2022 Nov 22.
Artigo em Inglês | MEDLINE | ID: mdl-36414003

RESUMO

18ß-Glycyrrhetinic acid (GA) is a triterpenoid possessing an anti-inflammatory activity in vivo, while the low bioavailability limits its application due to its intestinal accumulation. In order to investigate the metabolism of GA in intestinal microbes, it was incubated with human intestinal fungus Aspergillus niger RG13B1, finally leading to the isolation and identification of three new metabolites (1-3) and three known metabolites (4-6) based on 1D and 2D NMR and high-resolution electrospray ionization mass spectroscopy spectra. Metabolite 6 could target myeloid differentiation protein 2 (MD2) to suppress the activation of nuclear factor-kappa B (NF-κB) signaling pathway via inhibiting the nuclear translocation of p65 to downregulate its target proteins and genes in lipopolysaccharide (LPS)-mediated RAW264.7 cells. Molecular dynamics suggested that metabolite 6 interacted with MD2 through the hydrogen bond of amino acid residue Arg90. These findings demonstrated that metabolite 6 could serve as a potential candidate to develop the new inhibitors of MD2.

19.
RSC Adv ; 12(51): 33276-33283, 2022 Nov 15.
Artigo em Inglês | MEDLINE | ID: mdl-36425210

RESUMO

In this study, a series of mesoporous acidic polymeric ionic liquids were successfully synthesized and characterized to explore their structures and properties. Examination of catalytic performance using cyclohexanone oxime's maximum conversion were investigated, and the Box-Behnken design was used to achieve the highest hydrolysis conversion. Excellent catalytic activity, structural stability, and an easy recovery feature were all displayed by the Poly(VBS-DVB)HSO4 catalyst. Additionally, a possible reaction pathway involving hydrogen protons was proposed for the present hydrolysis. Moreover, a series of ketoximes were also examined including acetone oxime, butanone oxime, cyclopentanone oxime and acetophenone oxime over Poly(VBS-DVB)HSO4 catalyst. The conversion of ketoxime was not less than 80.44%, and the results also demonstrated excellent catalytic performance. Synthesis of mesoporous acidic polymeric ionic catalysts with good properties would be very important for their applications.

20.
Front Cell Neurosci ; 16: 1006797, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36425664

RESUMO

Background: Working memory (WM) and attention deficits are both important features of schizophrenia. WM is closely related to attention, for it acted as an important characteristic in activating and manipulating WM. However, the knowledge of neural mechanisms underlying the relationship between WM and attention deficits in schizophrenia is poorly investigated. Methods: Graph theory was used to examine the network topology at the whole-brain and large-scale network levels among 125 schizophrenia patients with different severity of attention deficits (65 mild attention deficits; 46 moderate attention deficits; and 14 severe attention deficits) and 53 healthy controls (HCs) during an N-back WM task. These analyses were repeated in the same participants during the resting state. Results: In the WM task, there were omnibus differences in small-worldness and normalized clustering coefficient at a whole-brain level and normalized characterized path length of the default-mode network (DMN) among all groups. Post hoc analysis further indicated that all patient groups showed increased small-worldness and normalized clustering coefficient of the whole brain compared with HCs, and schizophrenia with severe attention deficits showed increased normalized characterized path length of the DMN compared with schizophrenia with mild attention deficits and HCs. However, these observations were not persisted under the resting state. Further correlation analyses indicated that the increased normalized characterized path length of the DMN was correlated with more severe attentional deficits and poorer accuracy of the WM task. Conclusion: Our research demonstrated that, compared with the schizophrenia patients with less attention deficits, disrupted integration of the DMN may more particularly underlie the WM deficits in schizophrenia patients with severe attention deficits.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...