Mammalian target of rapamycin (mTOR) regulates cell proliferation, autophagy, and apoptosis by participating in multiple signaling pathways in the body. Studies have shown that the mTOR signaling ...pathway is also associated with cancer, arthritis, insulin resistance, osteoporosis, and other diseases. The mTOR signaling pathway, which is often activated in tumors, not only regulates gene transcription and protein synthesis to regulate cell proliferation and immune cell differentiation but also plays an important role in tumor metabolism. Therefore, the mTOR signaling pathway is a hot target in anti-tumor therapy research. In recent years, a variety of newly discovered mTOR inhibitors have entered clinical studies, and a variety of drugs have been proven to have high activity in combination with mTOR inhibitors. The purpose of this review is to introduce the role of mTOR signaling pathway on apoptosis, autophagy, growth, and metabolism of tumor cells, and to introduce the research progress of mTOR inhibitors in the tumor field.
In this paper, the parabolic equation with oblique derivative boundary condition is considered. The long time behavior of the solution is derived by selecting the appropriate auxiliary functions and ...making priori estimates. Through blow up analysis, time-dependent gradient estimates are obtained, followed by second-order derivative estimates. Then, the convergence of smooth solution to parabolic equations with the oblique derivative boundary condition is obtained using standard theory.
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•Three main preparation strategies of S-MOFs are summarized.•Representative applications of S-MOFs as advanced adsorbents are listed.•Three further trends in S-MOFs are stated.
...Metal-organic frameworks (MOFs) are a class of crystalline inorganic-organic hybrid porous materials. Sulfur-functionalized MOFs (S-MOFs) are a subclass of MOFs that show some distinctive advantages and extensively studied in solid-phase extraction. In this review, we present a summary on the synthesis and adsorptive application of S-MOFs, and highlight the benefits of sulfur-functionalization. Three most widely used synthesis strategies, namely direct synthesis, post-synthetic modification and composite materials are developed to prepare S-MOFs. Based on hard-soft-acid-base (HSAB) theory, S-MOFs find practical applications in the adsorption of heavy metal ions, especially for mercury. Besides, efficient adsorption of inorganic non-metallic compounds and organic molecules is also reported. Finally, challenges and further perspectives of S-MOFs are presented and discussed in detail to achieve better advancement.
Industry-education integration, is a teaching practice mode integrating talent training, scientific research and social service. In order to serve the orientation of high-level applied university in ...the statistics major of North China University of Technology, we have put forward 4 dimensions of industry-education integration in practical teaching, namely, curriculum teaching practice, practical teaching links, school-enterprise cooperation projects, and statistical discipline competitions. Further, the process of providing service products for society by statistics specialty is divided into four stages, that is, opportunity identification, product design, product launch and product evaluation, which corresponding to the four dimensions of industry-education integration respectively. Finally, the time-space association among the four dimensions is analyzed, and a benign and orderly operation mechanism of industry-education integration is constructed.
Single-atom Fe-N-C catalysts has attracted widespread attentions in the oxygen reduction reaction (ORR). However, the origin of ORR activity on Fe-N-C catalysts is still unclear, which hinder the ...further improvement of Fe-N-C catalysts. Herein, we provide a model to understand the ORR activity of Fe-N
site from the spatial structure and energy level of the frontier orbitals by density functional theory calculations. Taking the regulation of divacancy defects on Fe-N
site ORR activity as examples, we demonstrate that the hybridization between Fe 3dz
, 3dyz (3dxz) and O
π* orbitals is the origin of Fe-N
ORR activity. We found that the Fe-O bond length, the d-band center gap of spin states, the magnetic moment of Fe site and *O
as descriptors can accurately predict the ORR activity of Fe-N
site. Furthermore, these descriptors and ORR activity of Fe-N
site are mainly distributed in two regions with obvious difference, which greatly relate to the height of Fe 3d projected orbital in the Z direction. This work provides a new insight into the ORR activity of single-atom M-N-C catalysts.
•Three novel ACE inhibitory peptides were identified from hazelnut protein.•YLVR had highest ACE inhibitory activity with IC50 value of 15.42 μM.•Cation-pi interaction was crucial to binding affinity ...between peptide and ACE.
The mechanism of action of food-derived angiotensin-I-converting enzyme (ACE) inhibitory peptides has not been completely elucidated. In the present study, ion-exchange chromatography, gel filtration chromatography, reverse phase-high performance liquid chromatography, and liquid chromatography-electrospray ionization–tandem mass (LC-ESI-MS/MS) were employed for purifying and identifying the ACE inhibitory peptides from hazelnut. To understand the mode of action of these peptides, ACE inhibition kinetics, in vitro and in vivo bioavailability assays, active site analysis, and interaction between the inhibitory peptides and ACE were investigated. The results identified novel ACE inhibitory peptides Ala-Val-Lys-Val-Leu (AVKVL), Tyr-Leu-Val-Arg (YLVR), and Thr-Leu-Val-Gly-Arg (TLVGR) with IC50 values of 73.06, 15.42, and 249.3 μM, respectively. All peptides inhibited the ACE activity via a non-competitive mode. The binding free energies of AVKVL, YLVR, and TLVGR for ACE were −3.46, −6.48, and −7.37 kcal/mol, respectively. The strong inhibition of ACE by YLVR may be attributed to the formation of cation–pi interactions.
We investigate the internal decadal variability of the ocean carbon uptake using 100 ensemble simulations based on the Max Planck Institute Earth system model (MPI‐ESM). We find that on decadal time ...scales, internal variability (ensemble spread) is as large as the forced temporal variability (ensemble mean), and the largest internal variability is found in major carbon sink regions, that is, the 50–65°S band of the Southern Ocean, the North Pacific, and the North Atlantic. The MPI‐ESM ensemble produces both positive and negative 10 year trends in the ocean carbon uptake in agreement with observational estimates. Negative decadal trends are projected to occur in the future under RCP4.5 scenario. Due to the large internal variability, the Southern Ocean and the North Pacific require the most ensemble members (more than 53 and 46, respectively) to reproduce the forced decadal trends. This number increases up to 79 in future decades as CO2 emission trajectory changes.
Key Points
MPI‐ESM large ensemble simulates negative and positive decadal trends of carbon uptake in the current and the future ocean
Largest internal variability in the ocean carbon uptake is found in the Southern Ocean, the North Pacific, and the North Atlantic
The Southern Ocean and North Pacific require the largest number of ensembles from 46 to 79 to capture decadal forced (ensemble mean) signal
Rolling bearings are the core components of rotating machinery. Their health directly affects the performance, stability and life of rotating machinery. To prevent possible damage, it is necessary to ...detect the condition of rolling bearings for fault diagnosis. With the rapid development of intelligent fault diagnosis technology, various deep learning methods have been applied in fault diagnosis in recent years. Convolution neural networks (CNN) have shown high performance in feature extraction. However, the pooling operation of CNN can lead to the loss of much valuable information and the relationship between the whole and the part may be ignored. In this study, we proposed CNNEPDNN, a novel bearing fault diagnosis model based on ensemble deep neural network (DNN) and CNN. We firstly trained CNNEPDNN model. Each of its local networks was trained with different training datasets. The CNN used vibration sensor signals as the input, whereas the DNN used nine time-domain statistical features from bearing vibration sensor signals as the input. Each local network of CNNEPDNN extracted different features from its own trained dataset, thus we fused features with different discrimination for fault recognition. CNNEPDNN was tested under 10 fault conditions based on the bearing data from Bearing Data Center of Case Western Reserve University (CWRU). To evaluate the proposed model, four aspects were analyzed: convergence speed of training loss function, test accuracy, F-Score and the feature clustering result by t-distributed stochastic neighbor embedding (t-SNE) visualization. The training loss function of the proposed model converged more quickly than the local models under different loads. The test accuracy of the proposed model is better than that of CNN, DNN and BPNN. The F-Score value of the model is higher than that of CNN model, and the feature clustering effect of the proposed model was better than that of CNN.
Herbicides have been increasingly used worldwide and a large amount of herbicide residue eventually enters the ocean via groundwater or surface run-off every year. However, the global coastal ...pollution status of herbicides and their negative impact on marine life (especially phytoplankton) in natural environmental concentrations are poorly understood except for few special environments (e.g. the Great Barrier Reef, Australia). Our field investigation of the distribution of ten triazine herbicides in the Bohai Sea and the Yellow Sea of China revealed that the concentrations of triazine herbicides exceeded the “No Observed Effect Concentrations” for phytoplankton. Their total concentrations could be as high as 6.61 nmol L−1. Based on the concentration addition model, the toxicity of herbicide homologues is usually cumulative, and the combined toxicity of these ten triazine herbicides could cause 13.2% inhibition on the chlorophyll a fluorescence intensity of a representative diatom species Phaeodactylum tricornutum Pt-1, which corresponds roughly to the toxicity of atrazine in an equivalent concentration of 14.08 nmol L−1. Atrazine in this equivalent-effect concentration could greatly inhibit the growth of cells, the maximum quantum efficiency of photosystem II (Fv/Fm), and nutrient absorption of Phaeodactylum tricornutum Pt-1. Transcriptome analysis revealed that multiple metabolic pathways (Calvin cycle, tricarboxylic acid (TCA) cycle, glycolysis/gluconeogenesis, etc.) related with photosynthesis and carbon metabolism were greatly disturbed, which might ultimately influence the primary productivity of coastal waters. Moreover, with the values of its bioaccumulation factor ranging from 69.6 to 118.9, atrazine was found to be accumulated in algal cells, which indicates that herbicide pollution might eventually affect the marine food web and even threaten the seafood safety of human beings.
Abbreviations: CAGR, Compound annual growth rate (%); PS I/II, photosystem I/II; N, NO3-N, NO2-N, and NH4-N; P, PO4-P; Si, SiO4-Si. Data on global herbicide usage in this figure are from the databases of the Food and Agriculture Organization of the United Nations (http://www.fao.org/statistics/databases/en/) and the following references (Gu and Wang, 2016; Archbold and Nosarzewski, 2018; GlobeNewswire, 2017). Display omitted
•Total concentration of 10 triazine herbicides in coastal waters reached risk levels.•Triazine herbicides at environmental concentrations showed toxic effects on diatom.•Atrazine can be highly accumulated in algal cells.•The photosynthesis and carbon metabolism of diatom were significantly disturbed.•Coastal pollution of herbicide is a growing threat to primary productivity.
Abstract
Iron phthalocyanine (FePc) is a promising non-precious catalyst for the oxygen reduction reaction (ORR). Unfortunately, FePc with plane-symmetric FeN
4
site usually exhibits an ...unsatisfactory ORR activity due to its poor O
2
adsorption and activation. Here, we report an axial Fe–O coordination induced electronic localization strategy to improve its O
2
adsorption, activation and thus the ORR performance. Theoretical calculations indicate that the Fe–O coordination evokes the electronic localization among the axial direction of O–FeN
4
sites to enhance O
2
adsorption and activation. To realize this speculation, FePc is coordinated with an oxidized carbon. Synchrotron X-ray absorption and Mössbauer spectra validate Fe–O coordination between FePc and carbon. The obtained catalyst exhibits fast kinetics for O
2
adsorption and activation with an ultralow Tafel slope of 27.5 mV dec
−1
and a remarkable half-wave potential of 0.90 V. This work offers a new strategy to regulate catalytic sites for better performance.
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