Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: the case of Sana'a metropolitan city, Yemen.

An effective and efficient planning of an urban growth and land use changes and its impact on the environment requires information about growth trends and patterns amongst other important information. Over the years, many urban growth models have been developed and used in the developed countries for forecasting growth patterns. In the developing countries however, there exist a very few studies showing the application of these models and their performances. In this study two models such as cellular automata (CA) and the SLEUTH models are applied in a geographical information system (GIS) to simulate and predict the urban growth and land use change for the City of Sana’a (Yemen) for the period 2004–2020. GIS based maps were generated for the urban growth pattern of the city which was further analyzed using geo-statistical techniques. During the models calibration process, a total of 35 years of time series dataset such as historical topographical maps, aerial photographs and satellite imageries was used to identify the parameters that influenced the urban growth. The validation result showed an overall accuracy of 99.6 %; with the producer’s accuracy of 83.3 % and the user’s accuracy 83.6 %. The SLEUTH model used the best fit growth rule parameters during the calibration to forecasting future urban growth pattern and generated various probability maps in which the individual grid cells are urbanized assuming unique “urban growth signatures”. The models generated future urban growth pattern and land use changes from the period 2004–2020. Both models proved effective in forecasting growth pattern that will be useful in planning and decision making. In comparison, the CA model growth pattern showed high density development, in which growth edges were filled and clusters were merged together to form a compact built-up area wherein less agricultural lands were included. On the contrary, the SLEUTH model growth pattern showed more urban sprawl and low-density development that included substantial areas of agricultural lands

The use of cystatin C to inhibit epithelial–mesenchymal transition and morphological transformation stimulated by transforming growth factor-β

INTRODUCTION: Transforming growth factor-β (TGF-β) is a potent suppressor of mammary epithelial cell (MEC) proliferation and is thus an inhibitor of mammary tumor formation. Malignant MECs typically evolve resistance to TGF-β-mediated growth arrest, enhancing their proliferation, invasion, and metastasis when stimulated by TGF-β. Recent findings suggest that therapeutics designed to antagonize TGF-β signaling may alleviate breast cancer progression, thereby improving the prognosis and treatment of breast cancer patients. We identified the cysteine protease inhibitor cystatin C (CystC) as a novel TGF-β type II receptor antagonist that inhibits TGF-β binding and signaling in normal and cancer cells. We hypothesized that the oncogenic activities of TGF-β, particularly its stimulation of mammary epithelial–mesenchymal transition (EMT), can be prevented by CystC. METHOD: Retroviral infection was used to constitutively express CystC or a CystC mutant impaired in its ability to inhibit cathepsin protease activity (namely Δ14CystC) in murine NMuMG MECs and in normal rat kidney (NRK) fibroblasts. The effect of recombinant CystC administration or CystC expression on TGF-β stimulation of NMuMG cell EMT in vitro was determined with immunofluorescence to monitor rearrangements of actin cytoskeletal architecture and E-cadherin expression. Soft-agar growth assays were performed to determine the effectiveness of CystC in preventing TGF-β stimulation of morphological transformation and anchorage-independent growth in NRK fibroblasts. Matrigel invasion assays were performed to determine the ability of CystC to inhibit NMuMG and NRK motility stimulated by TGF-β. RESULTS: CystC and Δ14CystC both inhibited NMuMG cell EMT and invasion stimulated by TGF-β by preventing actin cytoskeletal rearrangements and E-cadherin downregulation. Moreover, both CystC molecules completely antagonized TGF-β-mediated morphological transformation and anchorage-independent growth of NRK cells, and inhibited their invasion through synthetic basement membranes. Both CystC and Δ14CystC also inhibited TGF-β signaling in two tumorigenic human breast cancer cell lines. CONCLUSION: Our findings show that TGF-β stimulation of initiating metastatic events, including decreased cell polarization, reduced cell–cell contact, and elevated cell invasion and migration, are prevented by CystC treatment. Our findings also suggest that the future development of CystC or its peptide mimetics hold the potential to improve the therapeutic response of human breast cancers regulated by TGF-β

Interactions between ovine cathepsin L, cystatin C and à2-macroglobulin : potential role in the genital tract

International audienc

Interactions between ovine cathepsin L, cystatin C and à2-macroglobulin : potential role in the genital tract

International audienc