<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kumar, S.</style></author><author><style face="normal" font="default" size="100%">Patil, H. S.</style></author><author><style face="normal" font="default" size="100%">Sharma, P.</style></author><author><style face="normal" font="default" size="100%">Kumar, D.</style></author><author><style face="normal" font="default" size="100%">Dasari, Sreekanth</style></author><author><style face="normal" font="default" size="100%">Puranik, Vedavati G.</style></author><author><style face="normal" font="default" size="100%">Thulasiram, H. V.</style></author><author><style face="normal" font="default" size="100%">Kundu, G. C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Andrographolide inhibits osteopontin expression and breast tumor growth through down regulation of PI3 Kinase/Akt signaling pathway</style></title><secondary-title><style face="normal" font="default" size="100%">Current Molecular Medicine</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Andrographolide</style></keyword><keyword><style  face="normal" font="default" size="100%">angiogenesis and breast tumor</style></keyword><keyword><style  face="normal" font="default" size="100%">migration</style></keyword><keyword><style  face="normal" font="default" size="100%">osteopontin</style></keyword><keyword><style  face="normal" font="default" size="100%">PI 3 kinase</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">SEP</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">8</style></number><publisher><style face="normal" font="default" size="100%">BENTHAM SCIENCE PUBL LTD</style></publisher><pub-location><style face="normal" font="default" size="100%">EXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES</style></pub-location><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">952-966</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Breast cancer is one of the most common cancers among women in India and around the world. Despite recent advancement in the treatment of breast cancer, the results of chemotherapy to date remain unsatisfactory, prompting a need to identify natural agents that could target cancer efficiently with least side effects. Andrographolide (Andro) is one such molecule which has been shown to possess inhibitory effect on cancer cell growth. In this study, Andro, a natural diterpenoid lactone isolated from Andrographis paniculata has been shown to inhibit breast cancer cell proliferation, migration and arrest cell cycle at G2/M phase and induces apoptosis through caspase independent pathway. Our experimental evidences suggest that Andro attenuates endothelial cell motility and tumor-endothelial cell interaction. Moreover, Andro suppresses breast tumor growth in orthotopic NOD/SCID mice model. The anti-tumor activity of Andro in both in vitro and in vivo model was correlated with down regulation of PI3 kinase/Akt activation and inhibition of pro-angiogenic molecules such as OPN and VEGF expressions. Collectively, these results demonstrate that Andro may act as an effective anti-tumor and anti-angiogenic agent for the treatment of breast cancer.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;4.197&lt;/p&gt;</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Neha, H. K.</style></author><author><style face="normal" font="default" size="100%">Sardana, H. K.</style></author><author><style face="normal" font="default" size="100%">Dahiya, N.</style></author><author><style face="normal" font="default" size="100%">Dogra, N.</style></author><author><style face="normal" font="default" size="100%">Kanawade, R.</style></author><author><style face="normal" font="default" size="100%">Sharma, Y. P.</style></author><author><style face="normal" font="default" size="100%">Kumar, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Automated myocardial infarction and angina detection using second derivative of photoplethysmography</style></title><secondary-title><style face="normal" font="default" size="100%">Physical and Engineering Sciences in Medicine</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Artificial neural network</style></keyword><keyword><style  face="normal" font="default" size="100%">Myocardial infarction detection</style></keyword><keyword><style  face="normal" font="default" size="100%">PPG</style></keyword><keyword><style  face="normal" font="default" size="100%">SDPPG</style></keyword><keyword><style  face="normal" font="default" size="100%">Unstable angina detection</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">SEP</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">46</style></volume><pages><style face="normal" font="default" size="100%">1259-1269</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Photoplethysmography (PPG) based healthcare devices have gained enormous interest in the detection of cardiac abnormalities. Limited research has been implemented for myocardial infarction (MI) detection. Moreover, PPG-based detection of angina is still a research gap. PPG signals are not always informative. Therefore, this research work presents the use of PPG signals and their second derivative to evaluate myocardial infarction and angina using a novel set of morphological features. The obtained morphological features are fed onto the feed-forward artificial neural network for the identification of the type of MI and unstable angina (UA). The initial experiments have been carried out on non-ambulatory (public) subjects for feature extraction and later evaluated on ambulatory (self-generated) databases. The intended method attains accuracy, sensitivity, and specificity of 98%, 97%, 98% on the public database and 94%, 94%, 94% on the self-generated database. The result shows that the proposed set of features can detect MI and UA with significant accuracy.&lt;/p&gt;
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	Foreign&lt;/p&gt;
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	4.4&lt;/p&gt;
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