34 research outputs found
Long-term exposure to hypoxia inhibits tumor progression of lung cancer in rats and mice
<p>Abstract</p> <p>Background</p> <p>Hypoxia has been identified as a major negative factor for tumor progression in clinical observations and in animal studies. However, the precise role of hypoxia in tumor progression has not been fully explained. In this study, we extensively investigated the effect of long-term exposure to hypoxia on tumor progression <it>in vivo.</it></p> <p>Methods</p> <p>Rats bearing transplanted tumors consisting of A549 human lung cancer cells (lung cancer tumor) were exposed to hypoxia for different durations and different levels of oxygen. The tumor growth and metastasis were evaluated. We also treated A549 lung cancer cells (A549 cells) with chronic hypoxia and then implanted the hypoxia-pretreated cancer cells into mice. The effect of exposure to hypoxia on metastasis of Lewis lung carcinoma in mice was also investigated.</p> <p>Results</p> <p>We found that long-term exposure to hypoxia a) significantly inhibited lung cancer tumor growth in xenograft and orthotopic models in rats, b) significantly reduced lymphatic metastasis of the lung cancer in rats and decreased lung metastasis of Lewis lung carcinoma in mice, c) reduced lung cancer cell proliferation and cell cycle progression <it>in vitro</it>, d) decreased growth of the tumors from hypoxia-pretreated A549 cells, e) decreased Na<sup>+</sup>-K<sup>+ </sup>ATPase α1 expression in hypoxic lung cancer tumors, and f) increased expression of hypoxia inducible factors (HIF1α and HIF2α) but decreased microvessel density in the lung cancer tumors. In contrast to lung cancer, the growth of tumor from HCT116 human colon cancer cells (colon cancer tumor) was a) significantly enhanced in the same hypoxia conditions, accompanied by b) no significant change in expression of Na<sup>+</sup>-K<sup>+ </sup>ATPase α1, c) increased HIF1α expression (no HIF2α was detected) and d) increased microvessel density in the tumor tissues.</p> <p>Conclusions</p> <p>This study demonstrated that long-term exposure to hypoxia repressed tumor progression of the lung cancer from A549 cells and that decreased expression of Na<sup>+</sup>-K<sup>+ </sup>ATPase was involved in hypoxic inhibition of tumor progression. The results from this study provide new insights into the role of hypoxia in tumor progression and therapeutic strategies for cancer treatment.</p
Clinical pharmacology of cancer therapies in older adults
This abbreviated review outlines the physiologic changes associated with aging, and examines how these changes may affect the pharmacokinetics and pharmacodynamics of anticancer therapies. We also provide an overview of studies that have been conducted evaluating the pharmacology of anticancer therapies in older adults, and issue a call for further research
Mobile RAM and shape formation by programmable particles
In the distributed model Amoebot of programmable matter, the computational entities, called particles, are anonymous finite-state machines that operate and move on a hexagonal tessellation of the plane. In this paper we show how a constant number of such weak particles can simulate a powerful Turing-complete entity that is able to move on the plane while computing. We then show an application of our tool to the classical Shape-Formation problem, providing a new and much more general distributed solution. Indeed, while the existing algorithms allow to form only shapes made of arrangements of segments and triangles, our algorithm allows the particles to form also more abstract and general connected shapes, including circles and spirals, as well as fractal objects of non-integer dimension. In lieu of the existing impossibility results based on the symmetry of the initial configuration of the particles, our result provides a complete characterization of the connected shapes that can be formed by an initially simply connected set of particles. Furthermore, in the case of non-connected target shapes, we give almost-matching necessary and sufficient conditions for their formability
An Evolutionary View on Reversible Shift-Invariant Transformations
We consider the problem of evolving a particular kind of shift-invariant transformation â namely, Reversible Cellular Automata (RCA) defined by conserved landscape rules â using GA and GP. To this end, we employ three different optimization strategies: a single-objective approach carried out with GA and GP where only the reversibility constraint of marker CA is considered, a multi-objective approach based on GP where both reversibility and the Hamming weight are taken into account, and a lexicographic approach where GP first optimizes only the reversibility property until a conserved landscape rule is obtained, and then maximizes the Hamming weight while retaining reversibility. The results are discussed in the context of three different research questions stemming from exhaustive search experiments on conserved landscape CA, which concern (1) the difficulty of the associated optimization problem for GA and GP, (2) the utility of conserved landscape CA in the domain of cryptography and reversible computing, and (3) the relationship between the reversibility property and the Hamming weight.Virtual/online event due to COVID-19Cyber Securit