Effects of STI571 (gleevec) on pancreatic cancer cell growth

BACKGROUND: Pancreatic cancer is an aggressive malignancy characterized by low responsiveness to chemotherapy and radiotherapy. This resistance is partly due to the overexpression of several tyrosine kinase receptors and their ligands. STI571 has specific activity in inhibiting c-kit, PDGF and Abl receptor tyrosine kinases and has proven successful in the treatment of CML and GIST patients. Here, we investigated the potential role of STI571 in pancreatic cancer. RESULTS: The GI(50 )of STI571 as well as the effects of STI571 on growth factor actions in pancreatic cell lines were analyzed using the MTT assay. FACS analysis using Annexin and PI staining was performed to study cell cycle, apoptosis, and cell death. Western blot analysis was carried out to investigate MAP kinase and receptor tyrosine kinase phosphorylation. STI571 inhibited cell proliferation in pancreatic cancer cell lines with GI(50 )concentrations ranging from 17 to 31.5 microM. EGF, IGF-1, and FGF-2 but not PDGF exerted growth stimulatory effects in pancreatic cancer cell lines. STI571 only partly blocked these effects on cell growth, and did not abrogate growth factor-induced receptor and MAPK phosphorylation. CONCLUSION: Our data demonstrate that STI571 inhibits pancreatic cancer cell growth with high GI50 concentrations through tyrosine-kinase receptor independent pathways. The clinical application of STI571 in pancreatic cancer is therefore rather doubtful

Toxic Effects of Silica Nanoparticles on Zebrafish Embryos and Larvae

Silica nanoparticles (SiNPs) have been widely used in biomedical and biotechnological applications. Environmental exposure to nanomaterials is inevitable as they become part of our daily life. Therefore, it is necessary to investigate the possible toxic effects of SiNPs exposure. In this study, zebrafish embryos were treated with SiNPs (25, 50, 100, 200 μg/mL) during 4-96 hours post fertilization (hpf). Mortality, hatching rate, malformation and whole-embryo cellular death were detected. We also measured the larval behavior to analyze whether SiNPs had adverse effects on larvae locomotor activity. The results showed that as the exposure dosages increasing, the hatching rate of zebrafish embryos was decreased while the mortality and cell death were increased. Exposure to SiNPs caused embryonic malformations, including pericardial edema, yolk sac edema, tail and head malformation. The larval behavior testing showed that the total swimming distance was decreased in a dose-dependent manner. The lower dose (25 and 50 μg/mL SiNPs) produced substantial hyperactivity while the higher doses (100 and 200 μg/mL SiNPs) elicited remarkably hypoactivity in dark periods. In summary, our data indicated that SiNPs caused embryonic developmental toxicity, resulted in persistent effects on larval behavior. © 2013 Duan et al.published_or_final_versio

Intelligent cache and buffer optimization for mobile VR adaptive transmission in 5G edge computing networks

Virtual Reality (VR) is a key industry for the development of the digital economy in the future. Mobile VR has advantages in terms of mobility, lightweight and cost-effectiveness, which has gradually become the mainstream implementation of VR. In this paper, a mobile VR video adaptive transmission mechanism based on intelligent caching and hierarchical buffering strategy in Mobile Edge Computing (MEC)-equipped 5G networks is proposed, aiming at the low latency requirements of mobile VR services and flexible buffer management for VR video adaptive transmission. To support VR content proactive caching and intelligent buffer management, users' behavioral similarity and users’ head movement trajectory are jointly used for viewpoint prediction. The tile-based content is proactively cached in the MEC nodes based on the popularity of the VR content. Second, a hierarchical buffer-based adaptive update algorithm is presented, which jointly considers bandwidth, buffer, and predicted viewpoint status to update the tile chunk in client buffer. Then, according to the decomposition of the problem, the buffer update problem is modeled as an optimization problem, and the corresponding solution algorithms are presented. Finally, the simulation results show that the adaptive caching algorithm based on 5G intelligent edge and hierarchical buffer strategy can improve the user experience in the case of bandwidth fluctuations, and the proposed viewpoint prediction method can significantly improve the accuracy of viewpoint prediction by 15%

FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting

Kilometer-scale modeling of global atmosphere dynamics enables fine-grained weather forecasting and decreases the risk of disastrous weather and climate activity. Therefore, building a kilometer-scale global forecast model is a persistent pursuit in the meteorology domain. Active international efforts have been made in past decades to improve the spatial resolution of numerical weather models. Nonetheless, developing the higher resolution numerical model remains a long-standing challenge due to the substantial consumption of computational resources. Recent advances in data-driven global weather forecasting models utilize reanalysis data for model training and have demonstrated comparable or even higher forecasting skills than numerical models. However, they are all limited by the resolution of reanalysis data and incapable of generating higher-resolution forecasts. This work presents FengWu-GHR, the first data-driven global weather forecasting model running at the 0.09$^{\circ}$ horizontal resolution. FengWu-GHR introduces a novel approach that opens the door for operating ML-based high-resolution forecasts by inheriting prior knowledge from a pretrained low-resolution model. The hindcast of weather prediction in 2022 indicates that FengWu-GHR is superior to the IFS-HRES. Furthermore, evaluations on station observations and case studies of extreme events support the competitive operational forecasting skill of FengWu-GHR at the high resolution.Comment: 19 page

Study on the influence of ECMWF short-term forecast field assimilation on regional mesoscale model forecast

The forecast of the global numerical weather prediction model is often used as the background field to drive the regional mesoscale weather models, and its forecast quality has an important impact on the prediction skill of regional models. The mesoscale operational model in Central China uses the Global Forecast Field (NCEP GFS) of the US Center for Environmental Prediction as the background field, and its forecast accuracy needs to be improved. This paper proposes a method to improve the initial field of the model by using the three-dimensional variational method to assimilate the high-quality European Centre for Medium-range Weather Forecasts (ECMWF) fine-grid forecast field to improve the short-term forecasting ability of the model. At first, the error characters of the 12 h forecast products of NCEP GFS and ECMWF were analyzed by using sounding observations. The RMSE (root mean square error) of temperature, horizontal wind field and relative humidity of ECMWF 12 h forecast are smaller than those of NCEP GFS forecast. Second, sensitivity experiments of ECMWF forecast field assimilation with different resolutions were conducted. Finally, 1°×1° resolution was selected based on the sensitivity experiments and a series of the data assimilation experiments with 1°×1° resolution was performed for August 2021. The results are as follows. (1) The assimilation forecast of heavy rain from 11 to 13 August 2021 shows that after 12 hours of spin-up, the forecast error of the element field has been significantly improved, especially at the bottom of the model. The TS score of 12-36 h, 36-60 h and 60-84 h cumulative precipitation has a certain improvement, especially the forecast of rainstorm magnitude. (2) ECMWF forecast field assimilation sensitivity experiments with different resolutions show that the forecast effect of ECMWF forecast field with 1°×1° resolution is better than 0.5°×0.5° and 0.25°×0.25°. (3) A series of the data assimilation experiments for August 2021 shows that the assimilation of ECMWF 12 h 1°×1° predicted variables has a lower RMSE of the 12 h, 36 h and 60 h forecasted temperature, humidity and wind field in the vertical direction than the control experiments, and the TS score was significantly improved, especially for 50 mm heavy rain precipitation, with an increase of 13.33%, which can effectively improve the forecast skills of the Wuhan Mesoscale Model

Transcriptional and Functional Analysis of the Effects of Magnolol: Inhibition of Autolysis and Biofilms in Staphylococcus aureus

BACKGROUND: The targeting of Staphylococcus aureus biofilm structures are now gaining interest as an alternative strategy for developing new types of antimicrobial agents. Magnolol (MOL) shows inhibitory activity against S. aureus biofilms and Triton X-100-induced autolysis in vitro, although there are no data regarding the molecular mechanisms of MOL action in bacteria. METHODOLOGY/PRINCIPAL FINDINGS: The molecular basis of the markedly reduced autolytic phenotype and biofilm inhibition triggered by MOL were explored using transcriptomic analysis, and the transcription of important genes were verified by real-time RT-PCR. The inhibition of autolysis by MOL was evaluated using quantitative bacteriolytic assays and zymographic analysis, and antibiofilm activity assays and confocal laser scanning microscopy were used to elucidate the inhibition of biofilm formation caused by MOL in 20 clinical isolates or standard strains. The reduction in cidA, atl, sle1, and lytN transcript levels following MOL treatment was consistent with the induced expression of their autolytic repressors lrgA, lrgB, arlR, and sarA. MOL generally inhibited or reversed the expression of most of the genes involved in biofilm production. The growth of S. aureus strain ATCC 25923 in the presence of MOL dose-dependently led to decreases in Triton X-100-induced autolysis, extracellular murein hydrolase activity, and the amount of extracellular DNA (eDNA). MOL may impede biofilm formation by reducing the expression of cidA, a murein hydrolase regulator, to inhibit autolysis and eDNA release, or MOL may directly repress biofilm formation. CONCLUSIONS/SIGNIFICANCE: MOL shows in vitro antimicrobial activity against clinical and standard S. aureus strains grown in planktonic and biofilm cultures, suggesting that the structure of MOL may potentially be used as a basis for the development of drugs targeting biofilms