41 research outputs found
Evaluation of Quantitative EEG by Classification and Regression Trees to Characterize Responders to Antidepressant and Placebo Treatment
The study objective was to evaluate the usefulness of Classification and Regression Trees (CART), to classify clinical responders to antidepressant and placebo treatment, utilizing symptom severity and quantitative EEG (QEEG) data. Patients included 51 adults with unipolar depression who completed treatment trials using either fluoxetine, venlafaxine or placebo. Hamilton Depression Rating Scale (HAM-D) and single electrodes data were recorded at baseline, 2, 7, 14, 28 and 56 days. Patients were classified as medication and placebo responders or non-responders. CART analysis of HAM-D scores showed that patients with HAM-D scores lower than 13 by day 7 were more likely to be treatment responders to fluoxetine or venlafaxine compared to non-responders (p=0.001). Youdenâs index Îł revealed that CART models using QEEG measures were more accurate than HAM-D-based models. For patients given fluoxetine, patients with a decrease at day 2 in Ξ cordance at AF2 were classified by CART as treatment responders (p=0.02). For those receiving venlafaxine, CART identified a decrease in ÎŽ absolute power at day 7 at the PO2 region as characterizing treatment responders (p=0.01). Using all patients receiving medication, CART identified a decrease in ÎŽ absolute power at day 2 in the FP1 region as characteristic of nonresponse to medication (p=0.003). Optimal trees from the QEEG CART analysis primarily utilized cordance values, but also incorporated some ÎŽ absolute power values. The results of our study suggest that CART may be a useful method for identifying potential outcome predictors in the treatment of major depression
Massive stars as thermonuclear reactors and their explosions following core collapse
Nuclear reactions transform atomic nuclei inside stars. This is the process
of stellar nucleosynthesis. The basic concepts of determining nuclear reaction
rates inside stars are reviewed. How stars manage to burn their fuel so slowly
most of the time are also considered. Stellar thermonuclear reactions involving
protons in hydrostatic burning are discussed first. Then I discuss triple alpha
reactions in the helium burning stage. Carbon and oxygen survive in red giant
stars because of the nuclear structure of oxygen and neon. Further nuclear
burning of carbon, neon, oxygen and silicon in quiescent conditions are
discussed next. In the subsequent core-collapse phase, neutronization due to
electron capture from the top of the Fermi sea in a degenerate core takes
place. The expected signal of neutrinos from a nearby supernova is calculated.
The supernova often explodes inside a dense circumstellar medium, which is
established due to the progenitor star losing its outermost envelope in a
stellar wind or mass transfer in a binary system. The nature of the
circumstellar medium and the ejecta of the supernova and their dynamics are
revealed by observations in the optical, IR, radio, and X-ray bands, and I
discuss some of these observations and their interpretations.Comment: To be published in " Principles and Perspectives in Cosmochemistry"
Lecture Notes on Kodai School on Synthesis of Elements in Stars; ed. by Aruna
Goswami & Eswar Reddy, Springer Verlag, 2009. Contains 21 figure