Traditional Chinese medicine (TCM) has been practiced for thousands of years and at the present time is widely accepted as an alternative treatment for cancer. In this review, we sought to summarize ...the molecular and cellular mechanisms underlying the chemopreventive and therapeutic activity of TCM, especially that of the Chinese herbal medicine‐derived phytochemicals curcumin, resveratrol, and berberine. Numerous genes have been reported to be involved when using TCM treatments and so we have selectively highlighted the role of a number of oncogene and tumor suppressor genes in TCM therapy. In addition, the impact of TCM treatment on DNA methylation, histone modification, and the regulation of noncoding RNAs is discussed. Furthermore, we have highlighted studies of TCM therapy that modulate the tumor microenvironment and eliminate cancer stem cells. The information compiled in this review will serve as a solid foundation to formulate hypotheses for future studies on TCM‐based cancer therapy.
In this review, we try to summarize the molecular and cellular mechanisms underlying traditional Chinese medicine treatment from the perspective of gene to cell regulation. In the gene regulation, we emphasize the expression of oncogene and tumor suppressor genes, and epigenetic modifications; in the cell regulation, we highlight the effects of TCM treatment on the cancer stem cells and tumor microenvironment.
The montmorillonite-chitosan composite could provide hydrophobicity and functional groups to enhance the performances of montmorillonite in wastewater treatment. The composites showed good abilities ...to remove the pollutants, such as heavy metals and dyes. However, the comparative adsorption of multiple metals on the fixed C-content nanocomposite needs to be studied further. This paper presents the adsorption of Pb2+, Cu2+, and Cd2+ by the nanocomposite of chitosan saturated montmorillonte. The composite was synthetized and characterized by X-ray diffraction and Fourier transform infrared spectrometer. The kinetics (single and binary systems), thermodynamics and isotherm adsorption studies of the three cations on the nanocomposite were conducted, and the data were fitted with models. Results showed, the affinity sequence of the adsorption toward the 3 cations is Pb2+>Cu2+>Cd2+. Under most experimental conditions, one of the cations could enhance the adsorption of the other present in the binary system. The adsorption of the 3 cations could be best fitted with pseudo-second order equation. The metal adsorption is a heterogeneous and exothermic reaction on the surface of the composite, and Pb2+, Cu2+ adsorption are spontaneous reaction at 25–50°C.
•The composite had adsorption affinity sequence of Pb2+>Cu2+>Cd2+.•One would enhance another metal adsorption in PbCu and CuCd.•Adsorptions were both heterogeneous and exothermic reaction.
Latent Multi-view Subspace Clustering Changqing Zhang; Qinghua Hu; Huazhu Fu ...
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
2017-July
Conference Proceeding
In this paper, we propose a novel Latent Multi-view Subspace Clustering (LMSC) method, which clusters data points with latent representation and simultaneously explores underlying complementary ...information from multiple views. Unlike most existing single view subspace clustering methods that reconstruct data points using original features, our method seeks the underlying latent representation and simultaneously performs data reconstruction based on the learned latent representation. With the complementarity of multiple views, the latent representation could depict data themselves more comprehensively than each single view individually, accordingly makes subspace representation more accurate and robust as well. The proposed method is intuitive and can be optimized efficiently by using the Augmented Lagrangian Multiplier with Alternating Direction Minimization (ALM-ADM) algorithm. Extensive experiments on benchmark datasets have validated the effectiveness of our proposed method.
Dimensionality reduction aims to map the high-dimensional inputs onto a low-dimensional subspace, in which the similar points are close to each other and vice versa. In this paper, we focus on ...unsupervised dimensionality reduction for the data with multiple views, and propose a novel method, called Multi-view Dimensionality co-Reduction. Our method flexibly exploits the complementarity of multiple views during the dimensionality reduction and respects the similarity relationships between data points across these different views. The kernel matching constraint based on Hilbert-Schmidt Independence Criterion enhances the correlations and penalizes the disagreement of different views. Specifically, our method explores the correlations within each view independently, and maximizes the dependence among different views with kernel matching jointly. Thus, the locality within each view and the consistence between different views are guaranteed in the subspaces corresponding to different views. More importantly, benefiting from the kernel matching, our method need not depend on a common low-dimensional subspace, which is critical to reduce the influence of the unbalanced dimensionalities of multiple views. Specifically, our method explicitly produces individual low-dimensional projections for individual views, which could be applied for new coming data in the out-of-sample manner. Experiments on both clustering and recognition tasks demonstrate the advantages of the proposed method over the state-of-the-art approaches.
Most of the current metric learning methods are proposed for point-to-point distance (PPD) based classification. In many computer vision tasks, however, we need to measure the point-to-set distance ...(PSD) and even set-to-set distance (SSD) for classification. In this paper, we extend the PPD based Mahalanobis distance metric learning to PSD and SSD based ones, namely point-to-set distance metric learning (PSDML) and set-to-set distance metric learning (SSDML), and solve them under a unified optimization framework. First, we generate positive and negative sample pairs by computing the PSD and SSD between training samples. Then, we characterize each sample pair by its covariance matrix, and propose a covariance kernel based discriminative function. Finally, we tackle the PSDML and SSDML problems by using standard support vector machine solvers, making the metric learning very efficient for multiclass visual classification tasks. Experiments on gender classification, digit recognition, object categorization and face recognition show that the proposed metric learning methods can effectively enhance the performance of PSD and SSD based classification.
A Ag3PO4/GO/UiO–66–NH2(AGU) composite photocatalyst was prepared by an ultrasonic-assisted in situ precipitation method. The optical property, structure, composition, and morphology of photocatalysts ...were investigated using UV–vis diffuse reflectance spectroscopy, photoluminescence spectroscopy, electrochemical impedance spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, energy-dispersive spectrometry, transmission electron microscopy, Fourier transform infrared spectroscopy, and charge flow tracking by photodeposition of Pt and PbO2 nanoparticles. In comparison with Ag3PO4 and Ag3PO4/UiO–66–NH2(AU), the AGU composite photocatalyst showed heightened photocatalytic performance for the degradation of levofloxacin hydrochloride (LVF). The AGU photocatalyst (dosage: 0.8 g/L) with 1% mass content of graphene oxide (GO), the mass ratio of Ag3PO4 and UiO–66–NH2(U66N) reached 2:1, showed the highest photodegradation rate of 94.97% for 25 mg/L LVF after 60 min of visible light irradiation at pH = 6. The formation of a heterojunction and the addition of GO synergistically promote faster separation of electron–hole pairs, retain more active substances, and enhance the performance of the photocatalyst. Furthermore, the mechanism of the Z-scheme of the AGU composite photocatalytic is proposed.
A novel Ag
3
PO
4
/reduced graphene oxide/Bi
2
MoO
6
(Ag
3
PO
4
/RGO/Bi
2
MoO
6
) Z-scheme photocatalyst has been successfully prepared by a precipitation-solvothermal method. The composition, ...morphology, structure and optical properties of the ternary composite were thoroughly investigated. The obtained Ag
3
PO
4
/RGO/Bi
2
MoO
6
composite displayed significantly enhanced photocatalytic activity for the degradation of methylene blue (MB) under visible light irradiation, and its degradation rate (0.14575 min
−1
) was approximately 2.34, 2.63 and 4.97 times faster than that of the Ag
3
PO
4
/Bi
2
MoO
6
composite, pure Ag
3
PO
4
and Bi
2
MoO
6
, respectively. Meanwhile, the Ag
3
PO
4
/RGO/Bi
2
MoO
6
composite exhibited better stability compared with pure Ag
3
PO
4
after four consecutive reuses. In addition, it shows good photodegradation efficiency for five other dyes under visible light irradiation. The improved photocatalytic performance and stability could be ascribed to the larger surface area, extended visible-light absorption capability and high-efficiency separation of electron-hole pairs of the Ag
3
PO
4
/RGO/Bi
2
MoO
6
composite. Furthermore, RGO could act as a charge transmission bridge to accelerate the electron transfer from Ag
3
PO
4
to Bi
2
MoO
6
(Ag
3
PO
4
→ RGO → Bi
2
MoO
6
) in this Z-scheme system; thus the photocorrosion of Ag
3
PO
4
and the recombination of charge carriers were effectively suppressed. The energy band structure and free radical capturing experiments proved that the electrons in the conduction band (CB) of Bi
2
MoO
6
had stronger reducibility and the holes in the valence band (VB) of Ag
3
PO
4
had higher oxidizability. Simultaneously, combined with the results of PL spectroscopy and photoelectrochemical measurements, the mechanism of Z-scheme charge transfer in the Ag
3
PO
4
/RGO/Bi
2
MoO
6
composite was further confirmed. This study provides an idea for improving the anti-photocorrosion and photocatalytic performance of photosensitive semiconductors.
A novel Ag
3
PO
4
/reduced graphene oxide/Bi
2
MoO
6
(Ag
3
PO
4
/RGO/Bi
2
MoO
6
) Z-scheme photocatalyst has been successfully prepared by a precipitation-solvothermal method.
In this study, a passive radar system that detects flying targets is developed in order to solve the problems associated with traditional flying target detection systems (i.e., their large size, high ...power consumption, complex systems, and poor battlefield survivability). On the basis of target detection, the system uses the multipath signal (which is usually eliminated as an error term in navigation and positioning), enhances it by supporting information, and utilizes the multi-source characteristics of ordinary omnidirectional global navigation satellite system (GNSS) signals. The results of a validation experiment showed that the system is able to locate a passenger airplane and obtain its flight trajectory using only one GNSS receiving antenna. The system is characterized by its light weight (less than 5 kg), low power consumption, simple system, good portability, low cost, and 24/7 and all-weather work. It can be installed in large quantities and has good prospects for development.
To combat the spread of antibiotic resistance, methods that quantitatively assess the metabolism-inhibiting effects of drugs in a rapid and culture-independent manner are urgently needed. Here using ...four oral bacteria as models, we show that heavy water (D2O)-based single-cell Raman microspectroscopy (D2O-Raman) can probe bacterial response to different drugs using the Raman shift at the C–D (carbon–deuterium vibration) band in 2040 to 2300 cm–1 as a universal biomarker for metabolic activity at single-bacterial-cell resolution. The “minimum inhibitory concentration based on metabolic activity” (MIC-MA), defined as the minimal dose under which the median ΔC–D-ratio at 8 h of drug exposure is ≤0 and the standard deviation (SD) of the ΔC–D ratio among individual cells is ≤0.005, was proposed to evaluate the metabolism-inhibiting efficacy of drugs. In addition, heterogeneity index of MIC-MA (MIC-MA-HI), defined as SD of C–D ratio among individual cells, quantitatively assesses the among-cell heterogeneity of metabolic activity after drug regimens. When exposed to 1× MIC of sodium fluoride (NaF), 1× MIC of chlorhexidine (CHX), or 60× MIC of ampicillin, the cariogenic oral pathogen Streptococcus mutans UA159 ceased propagation yet remained metabolically highly active. This underscores the advantage of MIC-MA over the growth-based MIC in being able to detect the “nongrowing but metabolically active” (NGMA) cells that underlie many latent or recurring infections. Moreover, antibiotic susceptible and resistant S. mutans strains can be readily discriminated at as early as 0.5 h. Thus, D2O-Raman can serve as a universal method for rapid and quantitative assessment of antimicrobial effects based on general metabolic activity at single-cell resolution.
Gestational diabetes (GDM) is common in pregnancies due to the inflammation and oxidative stress-mediated insulin resistance. In the present study, GDM was induced in the Wistar rats by administering ...the streptozotocin to elucidate whether the administration of syringin (50 mg/kg/day) during pregnancy could improve maternal glycemia and protect against the complications of GDM. The animals were assessed for their morphological changes in the β-islets of Langerhans and their insulin-producing ability, inflammatory cytokine markers, and the involvement of TLR4/MyD88/NF-κB signaling pathway using RT-PCR. The results demonstrated that the onset of GDM demonstrated pancreatic tissue degeneration in the islets of Langerhans with a significant increase in oxidative stress and reduced antioxidant enzymes. Besides, the mRNA expression levels of TLR4, MyD88, NF-Kβ p65; NLRP3 mRNA were profoundly increased in GDM rats compared to normal pregnant rats. On the other hand, syringin administered GDM rats abrogated the oxidative stress and attenuated the level of the inflammatory cytokines. Intriguingly, the decrease in TLR4 expression and the downstream molecules of MyD88, NF-κB, and NLRP3 were also observed in syringin administered GDM rats that indicate the insulin secretion stimulatory actions of syringin through the suppression of TLR4 signaling. These novel findings of the study provide evidence that syringin could be a probable candidate to be used in the treatment of gestational diabetes in the future.
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