TEC

About: TEC is a research topic. Over the lifetime, 5119 publications have been published within this topic receiving 84696 citations.

Tumor endothelial cells with high aldehyde dehydrogenase activity show drug resistance

Abstract: Tumor blood vessels play an important role in tumor progression and metastasis. We previously reported that tumor endothelial cells (TEC) exhibit several altered phenotypes compared with normal endothelial cells (NEC). For example, TEC have chromosomal abnormalities and are resistant to several anticancer drugs. Furthermore, TEC contain stem cell-like populations with high aldehyde dehydrogenase (ALDH) activity (ALDHhigh TEC). ALDHhigh TEC have proangiogenic properties compared with ALDHlow TEC. However, the association between ALDHhigh TEC and drug resistance remains unclear. In the present study, we found that ALDH mRNA expression and activity were higher in both human and mouse TEC than in NEC. Human NEC:human microvascular endothelial cells (HMVEC) were treated with tumor-conditioned medium (tumor CM). The ALDHhigh population increased along with upregulation of stem-related genes such as multidrug resistance 1, CD90, ALP, and Oct-4. Tumor CM also induced sphere-forming ability in HMVEC. Platelet-derived growth factor (PDGF)-A in tumor CM was shown to induce ALDH expression in HMVEC. Finally, ALDHhigh TEC were resistant to fluorouracil (5-FU) in vitro and in vivo. ALDHhigh TEC showed a higher grade of aneuploidy compared with that in ALDHlow TEC. These results suggested that tumor-secreting factor increases ALDHhigh TEC populations that are resistant to 5-FU. Therefore, ALDHhigh TEC in tumor blood vessels might be an important target to overcome or prevent drug resistance.

Artificial neural network applications in ionospheric studies

Abstract: The ionosphere of Earth exhibits considerable spatial changes and has large temporal variability of various timescales related to the mechanisms of creation, decay and transport of space ionospheric plasma. Many techniques for modelling electron density profiles through entire ionosphere have been developed in order to solve the "age-old problem" of ionospheric physics which has not yet been fully solved. A new way to address this problem is by applying artificial intelligence methodologies to current large amounts of solar-terrestrial and ionospheric data. It is the aim of this paper to show by the most recent examples that modern development of numerical models for ionospheric monthly median long-term prediction and daily hourly short-term forecasting may proceed successfully applying the artificial neural networks. The performance of these techniques is illustrated with different artificial neural networks developed to model and predict the temporal and spatial variations of ionospheric critical frequency, f0F2 and Total Electron Content (TEC). Comparisons between results obtained by the proposed approaches and measured f0F2 and TEC data provide prospects for future applications of the artificial neural networks in ionospheric studies.

The response of the ionosphere to faint and bright solar flares as deduced from global GPS network data

Abstract: Results derived from analysing the ionosphere response to faint and bright solar flares are presented. The analysis used technology of a global detection of ionospheric effects from solar flares as developed by the authors, on the basis of phase measurements of the Total Electron Content (TEC) in the ionosphere using an international GPS network. The essence of the method is that use is made of appropriate filtering and a coherent processing of variations in the TEC which is determined from GPS data, simultaneously for the entire set of visible GPS satellites at all stations used in the analysis. This technique is useful for identifying the ionospheric response to faint solar flares (of X-ray class C) when the variation amplitude of the TEC response to separate line-on-sight to GPS satellite is comparable to the level of background fluctuations. The dependence of the TEC variation response amplitude on the bright flares location on the Sun is investigated.

On the application of differential phase measurements to study the zonal large scale wave structure (LSWS) in the ionospheric electron content

Abstract: [1] The GNU Radio Beacon Receiver (GRBR) Network has been recently established to provide coverage of Southeast Asia and Pacific low-latitude regions, with planned extensions into the Indian and African longitude sectors. With the availability of CERTO (Coherent Electromagnetic Radio Tomography) beacon transmissions from Communication/Navigation Outage Forecasting System (C/NOFS) satellite, which is in a unique low-inclination (13°) orbit, it is now possible to study zonal large scale wave structure (LSWS) in ionospheric total electron content (TEC) with fine spatial resolution over a wide longitudinal region. An automated procedure to determine absolute TEC from relative TEC measurements for low inclination CNOFS orbits has been implemented through a simple single station procedure for initial offset estimation, which is shown to be consistent with the better established two station method and with observations from a Digisonde. The LSWS is extracted by subtracting the background variation from longitudinal variation of TEC. The upwellings of LSWS manifest as depletions in the residual TEC variations. Further, these zonal structures have been found, in general, to be aligned with geomagnetic field lines, and the scintillation patches have been found to align with the west walls of TEC depletions. This spatial alignment recapitulates the premise that the observed zonal wave-like structures in TEC are the manifestations of bottom side LSWS. Hence, the methodology presented in this paper, would prove useful in future, to study the characteristics of LSWS on a regular basis.

The use of the international GPS network as the global detector (GLOBDET) simultaneously observing sudden ionospheric disturbances

Abstract: We developed a new technology for global detection of ionospheric disturbances, on the basis of phase measurements of the total electron content (TEC) along the line-of-sight (LOS) between the receiver on the ground and transmitters on the GPS satellites using an international GPS networks. Temporal dependencies of TEC with the time resolution of 30 s are obtained for a set of spaced receivers of the GPS network simultaneously for the entire set of visible satellites. These series are subjected to filtering in the selected range of oscillation periods using known algorithms for spatio-temporal analysis of signals. An analysis is made of the possibilities of using the GLOBDET when detecting the ionospheric response of solar flares. In this case it is best to make the coherent summation of the filtered series of TEC. Because of a statistical independence of the background fluctuations, the signal/noise ratio, when the flare effect is detected, is increased due to a coherent processing by at least the times, where N is the number of LOS.