Multidrug resistance of non-adherent cancer cells

Metastases are the cause of 90% of human cancer deaths. Cancer in _situ_ can usually be effectively removed by surgery. Once cancer cells disseminate from the original site and start to circulate in blood, lymph, or other body fluids, the disease becomes almost incurable. Here we show that cancer cells in a non-adherent, 3-dimentional growth pattern are highly drug resistant compared to their adherent counterparts that grow in monolayer, attaching to the wall of tissue culture plates. The non-adherent cancer cells retain the adhering potential and can attach to an appropriate surface to reacquire adherent phenotype. Once the non-adherent cancer cells become attached, they regain drug response, similar to the original adherent cells. A significant increase in the expression of CD133, CD44, Nanog, survivin, and thymidylate synthase was observed in the non-adherent cancer cells compared to their adherent counterparts, which may underlie the mechanisms of multidrug resistance of the cells. Since the non-adherent cancer cells cultured in vitro resemble the circulating metastatic cells in vivo in that both cells exhibit suspended non-adherent phenotype, possess re-attaching potential, and are highly drug resistant, we suggest that circulating metastatic cells can attach to an appropriate surface to gain adherent phenotype and subsequently acquire drug sensitivity. We propose that devices coated with cell attachment materials or small particles of extracellular matrix and collagen that mimic the structural framework of real human tissues to which cells can attach and grow may be able to stabilize the circulating metastatic cells. Once the metastatic cells undergo attachment and become adherent, they gain drug sensitivity and can be killed by anticancer drugs that are either administered to the blood or conjugated to the devices

Mathematical modeling to elucidate brain tumor abrogation by immunotherapy with T11 target structure

T11 Target structure (T11TS), a membrane glycoprotein isolated from sheep erythrocytes, reverses the immune suppressed state of brain tumor induced animals by boosting the functional status of the immune cells. This study aims at aiding in the design of more efficacious brain tumor therapies with T11 target structure. We propose a mathematical model for brain tumor (glioma) and the immune system interactions, which aims in designing efficacious brain tumor therapy. The model encompasses considerations of the interactive dynamics of macrophages, cytotoxic T lymphocytes, glioma cells, TGF-$\beta$, IFN-$\gamma$ and the T11TS. The system undergoes sensitivity analysis, that determines which state variables are sensitive to the given parameters and the parameters are estimated from the published data. Computer simulations were used for model verification and validation, which highlight the importance of T11 target structure in brain tumor therapy

Susceptibility and magnetoresistance measurements on ferro- and antiferro- magnetic materials

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Planar electromagnetic sensor based estimation of nitrate contamination in water sources using independent component analysis

The main advantages of electromagnetic sensors can be listed as low-cost, convenient, suitable for in-situ measurement system, rapid response, and high durability. In this paper, the output parameters of the planar electromagnetic sensor have been observed with different kind of water samples at different concentrations. The output parameters have been derived and tested to be incorporated with independent component analysis (ICA) and used as inputs for an analysis model. The analysis model targeted to estimate the amount of nitrate contamination in water samples with the assistance of ICA based on FastICA fixed point algorithm under the contrast functions of pow3, tanh, gauss, and skew. Nitrates sample in the form of ammonium nitrates (NH 4NO 3), each of different concentration between 5 mg and 20 mg dissolved in 1 litre of deionized water (Milli-Q) was used as one of the main references. The analysis model was tested with eight sets of mixed NH 4NO 3 and (NH 4) 2HPO 4 water samples. It is seen from the results that the model can acceptably detect the presence of nitrate added in Milli-Q water and capable of distinguishing the concentration level in the presence of other type of contamination. The system and approach presented in this paper has the potential to be used as a useful low-cost tool for water sources monitoring