The World Health Organization predicts that by 2030 COPD will be the world's fourth commonest cause of death, after heart disease, stroke, and AIDS, and the increase in deaths is predicted to be greater in developing countries than in affluent countries.

The neglect of COPD by clinicians, researchers, and drug companies, says Professor Barnes in his Essay in PLoS Medicine, "is largely because COPD is viewed as self-inflicted (by smoking) and also because the underlying disease process is generally perceived to be irreversible."

Smoking is not the only cause of COPD, he says, and yet there has been little research funding aimed at investigating other contributing factors, including genes and environmental toxins. "More research is needed into the underlying disease mechanisms, to identify the genetics of susceptibility and to identify new targets for treatment."

Attitudes towards COPD must change, says Professor Barnes. "The attitude that smoking-related lung diseases are self-induced and therefore less worthy of attention needs to be changed; this attitude does not appear to apply to the same extent to ischemic heart disease, diabetes, or obesity."

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Using a previously established conceptual framework of conjugation processes in an isolated environment, researchers created a new mathematical model of bacterial transport and conjugation that focused on subsurface bacteria colonizing surfaces, such as sand and soil grains. The UC-Davis research was funded by the National Science Foundation.

The new model was then used to re-interpret previously published conjugation data. The findings revealed that bacterial transport and colonization of surfaces is as important a controlling factor for gene spread as was the rate of conjugation itself.

It is important to consider all natural processes together when trying to predict rates of gene transfer, said Ginn.

"The model gives us a new tool for designing new experiments that reflect gene transfer in the real world, including such things as transport of cells in porous media of soils and aquifers," explained Massoudieh. "It also can be used for ,extrapolative, modeling to predict rates of gene transfer in certain cases, mainly environmental science scenarios, but also with relevance to some medical scenarios."

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