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Here, we study interactions between polyclonal activated T cells that are mediated by IL-2 extracellular feedback as a model system.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Using mathematical modeling we show that extracellular feedback can give rise to opposite outcomes: competition or cooperation between interacting T cells, depending on their relative levels of activation. Furthermore, the outcome of the interaction also depends on the relative timing of activation of the cells. A critical time window exists after which a cell that has been more strongly activated nevertheless cannot exclude an inferior competitor.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>In a number of experimental studies of polyclonal T-cell systems, outcomes ranging from cooperation to competition as well as time dependent competition were observed. Our model suggests that extracellular feedback can contribute to these observed behaviors as it translates quantitative differences in T cells\u2019 activation strength and in their relative activation time into qualitatively different outcomes. We propose extracellular feedback as a general mechanism that can balance speed and accuracy \u2013 choosing the most suitable responders out of a polyclonal population under the clock of an escalating threat.<\/jats:p><\/jats:sec>","DOI":"10.1186\/1752-0509-6-111","type":"journal-article","created":{"date-parts":[[2012,8,27]],"date-time":"2012-08-27T14:14:08Z","timestamp":1346076848000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Balancing speed and accuracy of polyclonal T cell activation: a role for extracellular feedback"],"prefix":"10.1186","volume":"6","author":[{"given":"Yonatan","family":"Savir","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nir","family":"Waysbort","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaron E","family":"Antebi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tsvi","family":"Tlusty","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nir","family":"Friedman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2012,8,27]]},"reference":[{"key":"967_CR1","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1146\/annurev.biophys.093008.131241","volume":"39","author":"K Sneppen","year":"2010","unstructured":"Sneppen K, Krishna S, Semsey S: Simplified Models of Biological Networks. 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