Consideration of all of these factors is necessary in order to improve the consistency of the conditioning effect and to better understand the outcomes of investigations with rTMS. These user-controlled sources of variability are discussed against the background of the mechanisms that are believed to drive the excitability changes. The mechanism behind synaptic
plasticity is commonly accepted as the driver of sustained excitability modulation PKC412 in vivo for rTMS and indeed, plasticity and rTMS share many characteristics, but definitive evidence is lacking for this. It is more likely that there is a multiplicity of mechanisms behind the action of rTMS. The different mechanisms interact with each other and this will contribute to the variability of this website rTMS-induced excitability changes. This review investigates the links between rTMS and synaptic plasticity, describes their
similarities and differences, and highlights a neglected contribution of the membrane potential.
In summary, the principal aims of this review are (i) to discuss the different experimental and subject-related factors that contribute to the variability of excitability modulation induced by rTMS, and (ii) to discuss a generalized underlying mechanism for the excitability modulation. (C) 2010 Elsevier Ltd. All rights reserved.”
“Objective: Patients with pathologic node-negative early lung cancer may be optimal candidates for sublobar resection. We aimed to identify predictors of pathologic lymph node involvement in clinical stage IA lung adenocarcinoma.
Methods: The data from a multicenter database of 502 patients with completely resected clinical stage IA lung adenocarcinoma were retrospectively analyzed to determine the relationship between the lymph
node metastasis status and tumor size on high-resolution computed tomography (HRCT) or maximum standardized uptake value (SUVmax) on [18F]-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (FDGPET/CT). Revised SUVmax was used click here to correct interinstitutional discrepancies.
Results: In multivariate analyses, either a solid tumor size on HRCT (P = .001) or an SUVmax on FDG-PET/CT (P = .049) was an independent predictor of lymph node metastasis. The predictive criteria of pathologic node-negative early lung cancer were a solid tumor size of less than 0.8 cm or an SUVmax of less than 1.5. Patients who met the predictive criteria of pathologic node-negative disease had less pathologic invasiveness, such as lymphatic, vascular, or pleural invasion (P < .001), and better disease-free survival (P < .0001) than those who did not, and 86 (40.4%) of the 213 patients with T1b (2-3 cm) tumors met the predictive criteria.
Conclusions: Either a solid tumor size or an SUVmax was a significant independent predictor of nodal involvement in clinical stage IA lung adenocarcinoma. The pathologic node-negative status criteria of a solid tumor size of less than 0.