Paris polyphylla extract inhibits proliferation and promotes apoptosis in A549 lung cancer cells

Purpose: To investigate the effect of Paris polyphylla extract (PPE) on proliferation and apoptosis in A549 human lung cancer cells.Methods: Morphological changes were examined by microscopy in A549 cells after exposure to PPE. Trypan blue staining of living cells was used to aid the construction of the cell growth curve after treatment with different concentrations of PPE. The influence of PPE on cell proliferation, apoptosis and cell cycle were determined by MTT assay. Protein expressions of key apoptosis-related enzymes were determined by immuno-cytochemical method.Results: PPE inhibited the growth of A549 lung cancer cells at a concentration range of 12.5 – 200.0 μg/mL. Flow cytometry revealed that PPE promoted apoptosis in A549 cells. The proportion of cells in G0/G1-phase increased significantly (p < 0.01), while the proportion of cells in S- and G2/M-phases decreased correspondingly, indicating that the cells were in G0/G1-phase arrest. Cell cycle arrest and apoptosis-inducing effect gradually increased with increase in PPE concentration. With increasing concentration of PPE, there was significant increase in the expressions of caspase-8, caspase-3 and caspase-9, but significant decrease in Ki-67, p21ras protein (p < 0.01).Conclusion: PPE exerts pronounced inhibitory activity on the proliferation of A549 lung cancer cells. It also induces apoptosis in A549 cells, most probably by a mechanism related to Ki-67 and p21 ras protein expression, and arrest of cell cycle in G0/G1-phase.Keywords: Paris polyphylla, Antitumor activity, Lung cancer, A549 cells, p21 ras protein expression, Caspase, Cell cycle arrest, Apoptosi

Mitigation of monocyte inflammation by inhibition of sodium phosphate co-transporter with phosphonoformic acid and parthenolide in diabetic nephropathy uremia

Purpose: To investigate the effect of sodium phosphate co-transporter (Pit-1) on the regulation of monocyte inflammation in diabetic nephropathy uremia (DNU) patients and the underlying principles of inflammatory immune response during DNU pathogenesis.Methods: The levels of CD14+ CD16+ and Pit-1 on peripheral blood mononuclear cells (PBMC) were measured by flow cytometry. Serum C-reactive protein (CRP) and 25(OH)D3 were detected by immunoturbidimetry while IL-6 and MCP-1 were assayed with enzyme-linked immunoassay (ELISA). The amounts of vitamin D receptors (VDRs) and Pit-1 mRNA in human acute monocytic leukemia cell lines (THP-1) were determined by quantitative real-time polymerase chain reaction (qRT-PCR), while western blot was utilized for measurement of NF-κB p65 and p-STAT5.Results: Compared to the healthy group, DNU patients showed markedly higher CD14+CD16+, Pit-1, CRP, IL-6 and MCP-1, while 25(OH) D3 was reduced. Following stimulation with PFA or PTN, comparison with DNU group revealed that THP-1 monocytes showed a significant down-regulation of Pit-1 (1.34 ± 0.06 for PFA; 1.60 ± 0.25 for PTN; p < 0.05); NF-κB p65 (2.65 ± 0.25 for PFA; 3.88 ± 0.13 for PTN; p < 0.01), p-STAT5 (2.49 ± 0.10 for PFA; 3.03 ± 0.09 for PTN; p < 0.01) and a significant decrease in levels of IL-6 (55.38 ± 3.22 for PFA, 68.68 ± 6.01 for PTN; p < 0.05); MCP-1( 39.67 ± 3.62 for PFA; 52.62 ± 5.00 for PTN; p < 0.01), except for VDR (0.64 ± 0.15 for PFA, 0.43 ± 0.03 for PTN; p < 0.05) .Conclusion: The level of expression of Pit-1 has a positive correlation with the level of inflammatory monocytes, which indicates that Pit-1 can be used as a new biomarker for DNU diagnosis. In addition, since Pit-1 is connected to NF-κB and STAT5 signaling pathways which are critical to inflammatory immune response, development of drugs that target Pit-1 could be an approach in developing new strategies for DNU therapy.Keywords: Pit-1, Diabetic nephropathy, Uremia, Monocytes, Inflammation, NF-κB, STAT

Multi-objective optimization based network control principles for identifying personalized drug targets with cancer

It is a big challenge to develop efficient models for identifying personalized drug targets (PDTs) from high-dimensional personalized genomic profile of individual patients. Recent structural network control principles have introduced a new approach to discover PDTs by selecting an optimal set of driver genes in personalized gene interaction network (PGIN). However, most of current methods only focus on controlling the system through a minimum driver-node set and ignore the existence of multiple candidate driver-node sets for therapeutic drug target identification in PGIN. Therefore, this paper proposed multi-objective optimization-based structural network control principles (MONCP) by considering minimum driver nodes and maximum prior-known drug-target information. To solve MONCP, a discrete multi-objective optimization problem is formulated with many constrained variables, and a novel evolutionary optimization model called LSCV-MCEA was developed by adapting a multi-tasking framework and a rankings-based fitness function method. With genomics data of patients with breast or lung cancer from The Cancer Genome Atlas database, the effectiveness of LSCV-MCEA was validated. The experimental results indicated that compared with other advanced methods, LSCV-MCEA can more effectively identify PDTs with the highest Area Under the Curve score for predicting clinically annotated combinatorial drugs. Meanwhile, LSCV-MCEA can more effectively solve MONCP than other evolutionary optimization methods in terms of algorithm convergence and diversity. Particularly, LSCV-MCEA can efficiently detect disease signals for individual patients with BRCA cancer. The study results show that multi-objective optimization can solve structural network control principles effectively and offer a new perspective for understanding tumor heterogeneity in cancer precision medicine.Comment: 15 pages, 8 figures; This work has been submitted to IEEE Transactions on Evolutionary Computatio

On Fatigue Detection for Air Traffic Controllers Based on Fuzzy Fusion of Multiple Features

Fatigue detection for air traffic controllers is an important yet challenging problem in aviation safety research. Most of the existing methods for this problem are based on facial features. In this paper, we propose an ensemble learning model that combines both facial features and voice features and design a fatigue detection method through multifeature fusion, referred to as Facial and Voice Stacking (FV-Stacking). Specifically, for facial features, we first use OpenCV and Dlib libraries to extract mouth and eye areas and then employ a combination of M-Convolutional Neural Network (M-CNN) and E-Convolutional Neural Network (E-CNN) to determine the state of mouth and eye closure based on five features, i.e., blinking times, average blinking time, average blinking interval, Percentage of Eyelid Closure over the Pupil over Time (PERCLOS), and Frequency of Open Mouth (FOM). For voice features, we extract the Mel-Frequency Cepstral Coefficients (MFCC) features of speech. Such facial features and voice features are fused through a carefully designed stacking model for fatigue detection. Real-life experiments are conducted on 14 air traffic controllers in Southwest Air Traffic Management Bureau of Civil Aviation of China. The results show that the proposed FV-Stacking method achieves a detection accuracy of 97%, while the best accuracy achieved by a single model is 92% and the best accuracy achieved by the state-of-the-art detection methods is 88%

Simulation study on the optical processes at deep-sea neutrino telescope sites

The performance of a large-scale water Cherenkov neutrino telescope relies heavily on the transparency of the surrounding water, quantified by its level of light absorption and scattering. A pathfinder experiment was carried out to measure the optical properties of deep seawater in South China Sea with light-emitting diodes (LEDs) as light sources, photon multiplier tubes (PMTs) and cameras as photon sensors. Here, we present an optical simulation program employing the Geant4 toolkit to understand the absorption and scattering processes in the deep seawater, which helps to extract the underlying optical properties from the experimental data. The simulation results are compared with the experimental data and show good agreements. We also verify the analysis methods that utilize various observables of the PMTs and the cameras with this simulation program, which can be easily adapted by other neutrino telescope pathfinder experiments and future large-scale detectors.Comment: 27 pages, 11 figure

Understanding health and social challenges for aging and long-term care in China

The second King’s College London Symposium on Ageing and Long-term Care in China was convened from 4 to 5th July 2019 at King’s College London in London. The aim of the Symposium was to have a better understanding of health and social challenges for aging and long-term care in China. This symposium draws research insights from a wide range of disciplines, including economics, public policy, demography, gerontology, public health and sociology. A total of 20 participants from eight countries, seek to identify the key issues and research priorities in the area of aging and long-term care in China. The results published here are a synthesis of the top four research areas that represent the perspectives from some of the leading researchers in the field. © The Author(s) 2020

Timing Is Critical for an Effective Anti-Metastatic Immunotherapy: The Decisive Role of IFNγ/STAT1-Mediated Activation of Autophagy

BACKGROUND: Immunotherapy is often recommended as an adjuvant treatment to reduce the chance of cancer recurrence or metastasis. Interestingly, timing is very important for a successful immunotherapy against metastasis, although the precise mechanism is still unknown. METHODS AND FINDINGS: Using a mouse model of melanoma metastasis induced by intravenous injection of B16-F10 cells, we investigated the mechanism responsible for the diverse efficacy of the prophylactic or therapeutic TLR4 and TLR9 agonist complex against metastasis. We found that the activation of TLR4 and TLR9 prevented, but did not reverse, metastasis because the potency of this combination was neither sufficient to overcome the tumor cell-educated immune tolerance nor to induce efficacious autophagy in tumor cells. The prophylactic application of the complex promoted antimetastatic immunity, leading to the autophagy-associated death of melanoma cells via IFNγ/STAT1 activation and attenuated tumor metastasis. IFNγ neutralization reversed the prophylactic benefit induced by the complex by suppressing STAT1 activation and attenuating autophagy in mice. However, the therapeutic application of the complex did not suppress metastasis because the complex could not reverse tumor cell-induced STAT3 activation and neither activate IFNγ/STAT1 signaling and autophagy. Suppressing STAT3 activation with the JAK/STAT antagonist AG490 restored the antimetastatic effect of the TLR4/9 agonist complex. Activation of autophagy after tumor inoculation by using rapamycin, with or without the TLR4/9 agonist complex, could suppress metastasis. CONCLUSION AND SIGNIFICANCE: Our studies suggest that activation of IFNγ/STAT1 signaling and induction of autophagy are critical for an efficacious anti-metastatic immunotherapy and that autophagy activators may overcome the timing barrier for immunotherapy against metastasis