In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

Input: Consider Input: Context: Strontium ranelate reduces fracture risk in postmenopausal women with osteoporosis. Evidence from non-clinical studies and analyses of bone markers in phase III trials indicate that this is due to an increase in osteoblast formation and a decrease of osteoclastic resorption. The aim of this work was to investigate, in human cells, the mechanisms by which strontium ranelate is able to influence the activities of osteoblasts and osteoclasts.', 'Human primary osteoblasts were used to examine effects of strontium ranelate on replication (thymidine incorporation), differentiation (Runx2 and alkaline phosphatase) and cell survival (cell counts and caspase activity). Osteoprotegerin (OPG) was measured by quantitative reverse transcription PCR (qRT-PCR) and elisa and receptor activator of NFkappaB ligand (RANKL) by qRT-PCR and Western blot. As strontium ranelate has been proposed as an agonist of the calcium-sensing receptor (CaSR), the involvement of CaSR in the effects of strontium ranelate on OPG and RANKL expression, and cell replication was examined using siRNA.', 'Strontium ranelate increased mRNA and protein levels of OPG and suppressed those of RANKL. Strontium ranelate also stimulated osteoblast replication and differentiation and increased cell survival under stress. Knocking down CaSR suppressed strontium ranelate-induced stimulation of OPG mRNA, reduction of RANKL mRNA, and increase in replication, indicating the involvement of CaSR in these responses.\Question: Do osteoblasts play key roles in the mechanisms of action of strontium ranelate?

Output: Our results demonstrate that osteoblasts play a key role in the mechanism of action of the anti-fracture agent, strontium ranelate by mediating both its anabolic and anti-resorptive actions, at least in part, via activation of CaSR.

Input: Consider Input: Context: Intravenous tissue-type plasminogen activator (tPA) is a proven treatment for acute ischemic stroke, but there has been limited evaluation among patients aged 90 years.', 'We analyzed data from the Get With The Guidelines-Stroke national quality improvement registry from January 2009 to April 2013. Frequency, determinants, and outcomes of tPA use were compared among patients aged 90 and 3 younger age groups (18-64, 65-79, and 80-89 years).', 'Among 35708 patients from 1178 sites who arrived within 2 hours of time last known well and received tPA, 2585 (7.2%) were 90 years. Compared with younger patients, the rate of tPA use among patients without a documented contraindication was lower among patients aged 90 years (67.4% versus 84.1% in 18-89-year olds; P<0.0001). Discharge outcomes among individuals aged 90 years included discharge to home or acute rehabilitation in 31.4%, independent ambulation at discharge in 13.4%, symptomatic hemorrhage in 6.1%, and in-hospital mortality or hospice discharge in 36.4%. On multivariable analysis, good functional outcomes generally occurred less often and mortality more often among patients aged 90 years. The risk of symptomatic hemorrhage was increased compared with patients <65 years but was not significantly different than the risk in 66- to 89-year olds.\Question: Do use and Outcomes of Intravenous Thrombolysis for Acute Ischemic Stroke in Patients 90 Years of Age?

Output: The use of intravenous tPA among those aged 90 years is lower than in younger patients. When fibrinolytic therapy is used, the risk of symptomatic hemorrhage is not higher than in 66- to 89-year olds; however, mortality is higher and functional outcomes are lower.

Input: Consider Input: Context: Network component analysis (NCA) became a popular tool to understand complex regulatory networks. The method uses high-throughput gene expression data and a priori topology to reconstruct transcription factor activity profiles. Current NCA algorithms are constrained by several conditions posed on the network topology, to guarantee unique reconstruction (termed compliancy). However, the restrictions these conditions pose are not necessarily true from biological perspective and they force network size reduction, pruning potentially important components.', 'To address this, we developed a novel, Iterative Sub-Network Component Analysis (ISNCA) for reconstructing networks at any size. By dividing the initial network into smaller, compliant subnetworks, the algorithm first predicts the reconstruction of each subnetwork using standard NCA algorithms. It then subtracts from the reconstruction the contribution of the shared components from the other subnetwork. We tested the ISNCA on real, large datasets using various NCA algorithms. The size of the networks we tested and the accuracy of the reconstruction increased significantly. Importantly, FOXA1, ATF2, ATF3 and many other known key regulators in breast cancer could not be incorporated by any NCA algorithm because of the necessary conditions. However, their temporal activities could be reconstructed by our algorithm, and therefore their involvement in breast cancer could be analyzed.\Question: Does iterative sub-network component analysis enable reconstruction of large scale genetic networks?
Output: Our framework enables reconstruction of large gene expression data networks, without reducing their size or pruning potentially important components, and at the same time rendering the results more biological plausible. Our ISNCA method is not only suitable for prediction of key regulators in cancer studies, but it can be applied to any high-throughput gene expression data.