Assessing segmentation processes by click detection: online measure of statistical learning, or simple interference?

Statistical learning can be used to extract the words from continuous speech. Gómez, Bion, and Mehler (Language and Cognitive Processes, 26, 212–223, 2011) proposed an online measure of statistical learning: They superimposed auditory clicks on a continuous artificial speech stream made up of a random succession of trisyllabic nonwords. Participants were instructed to detect these clicks, which could be located either within or between words. The results showed that, over the length of exposure, reaction times (RTs) increased more for within-word than for between-word clicks. This result has been accounted for by means of statistical learning of the between-word boundaries. However, even though statistical learning occurs without an intention to learn, it nevertheless requires attentional resources. Therefore, this process could be affected by a concurrent task such as click detection. In the present study, we evaluated the extent to which the click detection task indeed reflects successful statistical learning. Our results suggest that the emergence of RT differences between within- and between-word click detection is neither systematic nor related to the successful segmentation of the artificial language. Therefore, instead of being an online measure of learning, the click detection task seems to interfere with the extraction of statistical regularities.

The impact of chemotherapy dose density and dose intensity on breast cancer outcome: what have we learned?

Optimising chemotherapy dose density and dose intensity are strategies aimed at improving outcomes in adjuvant therapy for patients with breast cancer. There are, in theory, at least five models allowing the delivery of a higher overall drug dose intensity. These are reviewed in this article and vary according to three main variables: the dose per course, the interval between doses and the total cumulative dose. Cyclophosphamide, anthracyclines and taxanes are among the most active agents for the treatment of breast cancer and, as such, they have been or are currently the focus of prospective, randomised clinical trials testing some of these dose-intensity models in the adjuvant setting. The results of recent trials suggest that anthracyclines, but not cyclophosphamide, are associated with better outcomes if used at higher doses per course and at higher cumulative doses. However, care has to be taken with premenopausal women where an increased dose of anthracycline per course but a reduced cumulative dose appears to produce a worse outcome. Moreover, decreasing the interval between doses, for anthracyclines and cyclophosphamide, does not seem to provide, so far, additional benefits for women with locally advanced breast cancer. This approach is not feasible with docetaxel, since an increase in dose density induces unwanted side-effects. These results represent our current state of knowledge, but clinical trials are being performed to evaluate further the effect of dose intensity, dose density and cumulative dose of key therapeutic agents on patient outcomes.

The impact of the Implantation of ICSI in the assited reproductive Technology

info:eu-repo/semantics/nonPublished