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109 results on '"Sivakumar, L."'

1. Tenecteplase versus standard of care for minor ischaemic stroke with proven occlusion (TEMPO-2): a randomised, open label, phase 3 superiority trial

Author

Salluzzi, Marina, Blenkin, Nicole, Dueck, Ashley, Doram, Craig, Zhang, Qiao, Kenney, Carol, Ryckborst, Karla, Bohn, Shelly, Collier, Quentin, Taylor, Frances, Lethebe, B. Cord, Jambula, Anitha, Sage, Kayla, Toussaint, Lana, Save, Supryia, Lee, Jaclyn, Laham, N, Sultan, A.A., Deepak, A., Sitaram, A., Demchuk, Andrew M., Lockey, A., Micielli, A., Wadhwa, A., Arabambi, B., Graham, B., Bogiatzi, Chrysi, Doshi, Darshan, Chakraborty, D., Kim, Diana, Vasquez, D, Singh, D, Tse, Dominic, Harrison, E., Smith, E.E., Teleg, E., Klourfeld, E., Klein, G., Sebastian, I.A., Evans, J, Hegedus, J, Kromm, J, Lin, K, Ignacio, K, Ghavami, Kimia, Ismail, M., Moores, M., Panzini, M.A., Boyko, M., Almekhlafi, M.A., Newcommon, Nancy, Maraj, N., Imoukhuede, O., Volny, O., Stys, Peter, Couillard, Phillipe, Ojha, P., Eswaradass, P., Joundi, Raed, Singh, R., Asuncion, R.M., Muir, R.T., Dey, S., Mansoor, S., Wasyliw, S., Nagendra, S., Hu, Sherry, Althubait, S., Chen, S., Bal, S., Van Gaal, Stephen, Peters, Steven, Ray, Sucharita, Chaturvedi, S., Subramaniam, Suresh, Fu, Vivian, Villaluna, K., Maclean, G., King-Azote, P., Ma, C., Plecash, A., Murphy, C., Gorman, J., Wilson, L., Zhou, L., Benevente, O., Teal, P., Yip, S., Mann, S., Dewar, B., Demetroff, M., Shamloul, R., Beardshaw, R., Roberts, S., Blaquiere, D., Stotts, G., Shamy, M., Bereznyakova, O., Fahed, R., Alesefir, W., Lavoie, Suzy, Hache, A., Collard, K, Mackey, A., Gosselin-Lefebvre, S., Verreault, S., Beauchamp, B., Lambourn, L., Khaw, A., Mai, L., Sposato, L., Bres Bullrich, M., Azarpazhooh, R., Fridman, S., Kapoor, A., Southwell, A., Bardi, E., Fatakdawala, I., Kamra, M, Lopes, K., Popel, N., Norouzi, V., Liu, A., Liddy, A.M., Ghoari, B., Hawkes, C., Enriquez, C.A., Gladstone, D.J., Manosalva Alzate, H.A., Khosravani, H., Hopyan, J.J., Sivakumar, K., Son, M., Boulos, M.I., Hamind, M.A., Swartz, R.H., Murphy, R., Reiter, S., Fitzpatrick, T., Bhandari, V., Good, J., Penn, M., Naylor, M., Frost, S., Cayley, A., Akthar, F., Williams, J., Kalman, L., Crellin, L., Wiegner, R., Singh, R.S., Stewart, T., To, W., Singh, S., Pikula, A., Jaigobin, C., Carpani, F., Silver, F., Janssen, H., Schaafsma, J., del Campo, M., Alskaini, M., Rajendram, P., Fairall, P., Granfield, B., Crawford, D., Jabs, J., White, L., Sivakumar, L., Piquette, L., Nguyen, T., Nomani, A., Wagner, A., Alrohimi, A., Butt, A., D'Souza, A., Gajurel, B., Vekhande, C., Kamble, H., Kalashyan, H., Lloret, M., Benguzzi, M., Arsalan, N., Ishaque, N., Ashayeriahmadabad, R., Samiento, R., Hosseini, S., Kazi, S., Das, S., Sugumar, T., Selchen, D., Kostyrko, P., Muccilli, A., Saposnik, A.G., Vandervelde, C., Ratnayake, K., McMillan, S., Katsanos, A., Shoamanesh, A., Sahlas, D.J., Naidoo, V., Todorov, V., Toma, H., Brar, J., Lee, J., Horton, M., Shand, E., Weatherby, S., Jin, A., Durafourt, B., Jalini, S., Gardner, A., Tyson, C., Junk, E., Foster, K., Bolt, K., Sylvain, N., Maley, S., Urroz, L., Peeling, L., Kelly, M., Whelan, R., Cooley, R., Teitelbaum, J., Boutayeb, A., Moore, A., Cole, E., Waxman, L., Ben-Amor, N., Sanchez, R., Khalil, S., Nehme, A., Legault, C., Tampieri, D., Ehrensperger, E., Vieira, L., Cortes, M., Angle, M., Hannouche, M., Badawy, M., Werner, K., Wieszmuellner, S., Langer, A., Gisold, A., Zach, H., Rommer, P., Macher, S., Blechinger, S., Marik, W., Series, W., Baumgartinger, M., Krebs, S., Koski, J., Eirola, S., Ivanoff, T., Erakanto, A., Kupari, L., Sibolt, G., Panula, J., Tomppo, L., Tiainen, M., Ahlstrom, M., Martinez Majander, N., Suomalainen, O., Raty, S., Levi, C., Kerr, E., Allen, J., Kaauwai, L.P., Belevski, L., Russell, M., Ormond, S., Chew, A., Loiselle, A., Royan, A., Hughes, B., Garcia Esperon, C., Pepper, E., Miteff, F., He, J., Lycett, M., Min, M., Murray, N., Pavey, N., Starling de Barros, R., Gangadharan, S., Dunkerton, S., Waller, S., Canento Sanchez, T., Wellings, T., Edmonds, G., Whittaker, K.A., Ewing, M., Lee, P., Singkang, R., McDonald, A., Dos Santos, A., Shin, C., Jackson, D., Tsoleridis, J., Fisicchia, L., Parsons, N., Shenoy, N., Smith, S., Sharobeam, A., Balabanski, A., Park, A., Williams, C., Pavlin-Premri, D., Rodrigues, E., Alemseged, F., Ng, F., Zhao, H., Beharry, J., Ng, J.L., Williamson, J., Wong, J.Z.W., Li, K., Kwan, M.K., Valente, M., Yassi, N., Yogendrakumar, V., McNamara, B., Buchanan, C., McCarthy, C., Thomas, G., Stephens, K., Chung, M., Chung, M.F., Tang, M., Busch, T., Frost, T., Lee, R., Stuart, N., Pachani, N., Menon, A., Borojevic, B., Linton, C.M., Garcia, G., Callaly, E.P., Dewey, H., Liu, J., Chen, J., Wong, J., Nowak, K., To, K., Lizak, N.S., Bhalala, O., Park, P., Tan, P., Martins, R., Cody, R., Forbes, R., Chen, S.K., Ooi, S., Tu, S., Dang, Y.L., Ling, Z., Cranefield, J., Drew, R., Tan, A., Kurunawai, C., Harvey, J., Mahadevan, J.J., Cagi, L., Palanikumar, L., Chia, L.N., Goh, R., El-Masri, S., Urbi, B., Rapier, C., Berrill, H., McEvoy, H., Dunning, R., Kuriakose, S., Chad, T., Sapaen, V., Sabet, A., Shah, D., Yeow, D., Lilley, K., Ward, K., Mozhy Mahizhnan, M., Tan, M., Lynch, C., Coveney, S., Tobin, K., McCabe, J., Marnane, M., Murphy, S., Large, M., Moynihan, B., Boyle, K., Sanjuan, E., Sanchis, M., Boned, S., Pancorbo, O., Sala, V., Garcia, L., Garcia-Tornel, A., Juega, J., Pagola, J., Santana, K., Requena, M., Muchada, M., Olive, M., Lozano, P.J., Rubiera, M., Deck, M., Rodriguez, N., Gomez, B., Reyes Munoz, F.J., Gomez, A.S., Sanz, A.C., Garcia, E.C., Penacoba, G., Ramos, M.E., de Lera Alfonso, M., Feliu, A, Pardo, L., Ramirez, P., Murillo, A., Lopez Dominguez, D., Rodriguez, J., Terceno Izaga, M., Reina, M., Viturro, S.B., Bojaryn, U., Vera Monge, V.A., Silva Blas, Y., R Siew, R., Agustin, S J, Seet, C., Tianming, T., d'Emden, A., Murray, A., Welch, A., Hatherley, K., Day, N., Smith, W., MacRae, E., Mitchell, E.S., Mahmood, A., Elliot, J., Neilson, S., Biswas, V., Brown, C., Lewis, A., Ashton, A., Werring, D., Perry, R., Muhammad, R., Lee, Y.C., Black, A., Robinson, A., Williams, A., Banaras, A., Cahoy, C., Raingold, G., Marinescu, M., Atang, N., Bason, N., Francia, N., Obarey, S., Feerick, S., Joseph, J., Schulz, U., Irons, R., Benjamin, J., Quinn, L., Jhoots, M., Teal, R., Ford, G., Harston, G., Bains, H., Gbinigie, I., Mathieson, P., Sim, C.H., Hayter, E., Kennedy, K., Binnie, L., Priestley, N., Williams, R., Ghatala, R., Stratton, S., Blight, A., Zhang, L., Davies, A., Duffy, H., Roberts, J., Homer, J., Roberts, K., Dodd, K., Cawley, K., Martin, M., Leason, S., Cotgreave, S., Taylor, T., Nallasivan, A., Haider, S., Chakraborty, T., Webster, T., Gil, A., Martin, B., Joseph, B., Cabrera, C., Jose, D., Man, J., Aquino, J., Sebastian, S., Osterdahl, M., Kwan, M., Matthew, M., Ike, N., Bello, P., Wilding, P., Fuentes, R., Shah, R., Mashate, S., Patel, T., Nwanguma, U., Dave, V., Haber, A., Lee, A., O'Sullivan, A., Drumm, B., Dawson, A.C., Matar, T., Roberts, D., Taylor, E., Rounis, E., El-Masry, A., O'Hare, C., Kalladka, D., Jamil, S., Auger, S., Raha, O., Evans, M., Vonberg, F., Kalam, S., Ali Sheikh, A., Jenkins, I.H., George, J., Kwan, J., Blagojevic, J., Saeed, M., Haji-Coll, M., Tsuda, M., Sayed, M., Winterkron, N., Thanbirajah, N., Vittay, O., Karim, R., Smail, R.C., Gauhar, S., Elmamoun, S., Malani, S., Pralhad Kelavkar, S., Hiden, J., Ferdinand, P., Sanyal, R., Varquez, R., Smith, B., Okechukwu, C., Fox, E., Collins, E., Courtney, K., Tauro, S., Patterson, C., McShane, D., Roberts, G., McIImoyle, J., McGuire, K., Fearon, P., Gordon, P., Isaacs, K., Lucas, K., Smith, L., Dews, L., Bates, M., Lawrence, S., Heeley, S., Patel, V., Chin, Y.M., Sims, D., Littleton, E., Khaira, J., Nadar, K., Kieliszkowska, A., Sari, B., Domingos Belo, C., Smith, E., Manolo, E.Y., Aeron-Thomas, J., Doheny, M., Garcia Pardo, M., Recaman, M., Tibajia, M.C., Aissa, M., Mah, Y., Yu, T., Meenakshisundaram, S., Heller, S., Alsukhni, R., Williams, O., Farag, M., Benger, M., Engineer, A., Bayhonan, S., Conway, S., Bhalla, A., Nouvakis, D., Theochari, E., Boyle, F., Teo, J., King-Robson, J., Law, K.Y., Sztriha, L., McGovern, A., Day, D., Mitchell-Douglas, J., Francis, J., Iqbal, A., Punjabivaryani, P., Anonuevo Reyes, J., Anonuevo Reyes, M., Pauls, M., Buch, A., Hedstrom, A., Hutchinson, C., Kirkland, C., Newham, J., Wilkes, G., Fleming, L., Fleck, N., Franca, A., Chwal, B., Oldoni, C., Mantovani, G., Noll, G., Zanella, L., Soma, M., Secchi, T., Borelli, W., Rimoli, B.P., da Cunha Silva, G.H., Machado Galvao Mondin, L.A., Barbosa Cerantola, R., Imthon, A.K., Esaki, A.S., Camilo, M., Vincenzi, O.C., ds Cruz, R.R., Morillos, M.B., Riccioppa Rodrigues, G.G., Santos Ferreira, K., Pazini, A.M., Pena Pereira, M.A., de Albuquerque, A.L.A., Massote Fontanini, C.E., Matinez Rubio, C.F., dos Santos, D.T., Dias, F.A., Alves, F.F.A., Milani, C., Pegorer Santos, B., Winckler, F., De Souza, J.T., Bonome, L.A.M., Cury Silva, V.A., Teodoro, R.S., Modolo, G.P., Ferreira, N.C., Barbosa dos Santos, D.F., dos Santos Moreira, J.C., Cruz Guedes de Morais, A.B., Vieira, J., Mendes, G., de Queiroz, J.P., Coutts, Shelagh B, Ankolekar, Sandeep, Appireddy, Ramana, Arenillas, Juan F, Assis, Zarina, Bailey, Peter, Barber, Philip A, Bazan, Rodrigo, Buck, Brian H, Butcher, Ken S, Camden, Marie-Christine, Campbell, Bruce C V, Casaubon, Leanne K, Catanese, Luciana, Chatterjee, Kausik, Choi, Philip M C, Clarke, Brian, Dowlatshahi, Dar, Ferrari, Julia, Field, Thalia S, Ganesh, Aravind, Ghia, Darshan, Goyal, Mayank, Greisenegger, Stefan, Halse, Omid, Horn, Mackenzie, Hunter, Gary, Imoukhuede, Oje, Kelly, Peter J, Kennedy, James, Kleinig, Timothy J, Krishnan, Kailash, Lima, Fabricio, Mandzia, Jennifer L, Marko, Martha, Martins, Sheila O, Medvedev, George, Menon, Bijoy K, Mishra, Sachin M, Molina, Carlos, Moussaddy, Aimen, Muir, Keith W, Parsons, Mark W, Penn, Andrew M W, Pille, Arthur, Pontes-Neto, Octávio M, Roffe, Christine, Serena, Joaquin, Simister, Robert, Singh, Nishita, Spratt, Neil, Strbian, Daniel, Tham, Carol H, Wiggam, M Ivan, Williams, David J, Willmot, Mark R, Wu, Teddy, Yu, Amy Y X, Zachariah, George, Zafar, Atif, Zerna, Charlotte, and Hill, Michael D

Published
2024
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3. Anticancer effect of fucoidan on cell proliferation, cell cycle progression, genetic damage and apoptotic cell death in HepG2 cancer cells

Author

Arumugam P., Arunkumar K., Sivakumar L., Murugan M., and Murugan K.

Subjects
Toxicology. Poisons, RA1190-1270
Abstract

The centre of the attraction of this article is inevitably associated with fucoidan polymers in terms of brown seaweed such as Turbinaria conoides. Fucoidan is a sulphated polysaccharide constitutes fucose as a major principle sugar along with other monosugars such as glucuronic acid, xylose and galactose. The core value of fucoidan in terms of various cancer types were substantially exhibited through targeting the key apoptotic molecules and subsequently mitigate the toxicity that are essentially included in the chemotherapeutic agents and radiation. The pragmatic investigation about the anti-cancer effect of fucoidan in a hepatoblastoma-derived (HepG2) cell line was thoroughly analyzed by the typical techniques such as cell viability, colony formation, cell migration, cell cycle progression, genetic damage and apoptosis along with their nuclear morphology and mitochondrial membrane potential. Following the analyzes, the cell viability was precisely evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. And hence, cell cycle arrest and apoptosis was appropriately examined staining with propidium iodide (PI) and annexin V-fluorescein isothiocyante (FITC) by flowcytometer, respectively. Primarily, genetic damage by fucoidan in HepG2 cell line was evaluated by following Trevigen’s comet assay kit. In addition, alteration of nuclear content and mitochondrial membrane potential were also detected with Hoechst and mitochondrial membrane potential dye (JC-1: 5,5′6,6′-tetrachloro-1,1′3,3′tetraethylbenzimi-dazolycarbocyanine iodide) by fluorescence microscopy, respectively. The results of the present study showed that cells constituted with fucoidan/quercetin standard at 50, 100 and 200 μg/ml exhibited cell viability about 71, 60 & 40/80, 65 & 45%, respectively. The above recorded effect of fucoidan was a concentration-dependant inhibition on the basis of decline in colony forming and cell migration potential of HepG2 cancer cells. Compared with untreated control, fucoidan consituted cells were significantly (p ≤ 0.05) accumulated proliferative cells in the G0/G1 phase of the cell cycle in a concentration dependent manner. Increasing concentration of fucoidan (50,100 and 200 μg/ml) was remarkably enhanced the DNA damage which reflected through tail moment value of 3.8, 7.1 & 12.8 folds with respect to the untreated control. Fucoidan induced total apoptotic cells were observed ∼20–40% at 50–200 μg/ml concentrations. The apoptotic cell formation effected by change in the nuclear content and mitochondrial membrane potential was confirmed in HepG2 cancer cells under fluorescence microscopy. It was eventually concluded that the fucoidan display promising anti-cancer activity against HepG2 cancer cells by promoting the inhibition of cell proliferation, migration and cell arrest on concentration dependent-manner that was well correlated with genetic damage and apoptosis. Keywords: Fucoidan, HepG2 cells, Cell cycle, Genetic damage, Apoptosis, Seaweed, Natural biopolymer

Published
2019
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4. Tenecteplase versus standard of care for minor ischaemic stroke with proven occlusion (TEMPO-2): a randomised, open label, phase 3 superiority trial

Author

Coutts, Shelagh B, Ankolekar, Sandeep, Appireddy, Ramana, Arenillas, Juan F, Assis, Zarina, Bailey, Peter, Barber, Philip A, Bazan, Rodrigo, Buck, Brian H, Butcher, Ken S, Camden, Marie-Christine, Campbell, Bruce C V, Casaubon, Leanne K, Catanese, Luciana, Chatterjee, Kausik, Choi, Philip M C, Clarke, Brian, Dowlatshahi, Dar, Ferrari, Julia, Field, Thalia S, Ganesh, Aravind, Ghia, Darshan, Goyal, Mayank, Greisenegger, Stefan, Halse, Omid, Horn, Mackenzie, Hunter, Gary, Imoukhuede, Oje, Kelly, Peter J, Kennedy, James, Kenney, Carol, Kleinig, Timothy J, Krishnan, Kailash, Lima, Fabricio, Mandzia, Jennifer L, Marko, Martha, Martins, Sheila O, Medvedev, George, Menon, Bijoy K, Mishra, Sachin M, Molina, Carlos, Moussaddy, Aimen, Muir, Keith W, Parsons, Mark W, Penn, Andrew M W, Pille, Arthur, Pontes-Neto, Octávio M, Roffe, Christine, Serena, Joaquin, Simister, Robert, Singh, Nishita, Spratt, Neil, Strbian, Daniel, Tham, Carol H, Wiggam, M Ivan, Williams, David J, Willmot, Mark R, Wu, Teddy, Yu, Amy Y X, Zachariah, George, Zafar, Atif, Zerna, Charlotte, Hill, Michael D, Salluzzi, Marina, Blenkin, Nicole, Dueck, Ashley, Doram, Craig, Zhang, Qiao, Kenney, Carol, Ryckborst, Karla, Bohn, Shelly, Collier, Quentin, Taylor, Frances, Lethebe, B. Cord, Jambula, Anitha, Sage, Kayla, Toussaint, Lana, Save, Supryia, Lee, Jaclyn, Laham, N, Sultan, A.A., Deepak, A., Sitaram, A., Demchuk, Andrew M., Lockey, A., Micielli, A., Wadhwa, A., Arabambi, B., Graham, B., Bogiatzi, Chrysi, Doshi, Darshan, Chakraborty, D., Kim, Diana, Vasquez, D, Singh, D, Tse, Dominic, Harrison, E., Smith, E.E., Teleg, E., Klourfeld, E., Klein, G., Sebastian, I.A., Evans, J, Hegedus, J, Kromm, J, Lin, K, Ignacio, K, Ghavami, Kimia, Ismail, M., Moores, M., Panzini, M.A., Boyko, M., Almekhlafi, M.A., Newcommon, Nancy, Maraj, N., Imoukhuede, O., Volny, O., Stys, Peter, Couillard, Phillipe, Ojha, P., Eswaradass, P., Joundi, Raed, Singh, R., Asuncion, R.M., Muir, R.T., Dey, S., Mansoor, S., Wasyliw, S., Nagendra, S., Hu, Sherry, Althubait, S., Chen, S., Bal, S., Van Gaal, Stephen, Peters, Steven, Ray, Sucharita, Chaturvedi, S., Subramaniam, Suresh, Fu, Vivian, Villaluna, K., Maclean, G., King-Azote, P., Ma, C., Plecash, A., Murphy, C., Gorman, J., Wilson, L., Zhou, L., Benevente, O., Teal, P., Yip, S., Mann, S., Dewar, B., Demetroff, M., Shamloul, R., Beardshaw, R., Roberts, S., Blaquiere, D., Stotts, G., Shamy, M., Bereznyakova, O., Fahed, R., Alesefir, W., Lavoie, Suzy, Hache, A., Collard, K, Mackey, A., Gosselin-Lefebvre, S., Verreault, S., Beauchamp, B., Lambourn, L., Khaw, A., Mai, L., Sposato, L., Bres Bullrich, M., Azarpazhooh, R., Fridman, S., Kapoor, A., Southwell, A., Bardi, E., Fatakdawala, I., Kamra, M, Lopes, K., Popel, N., Norouzi, V., Liu, A., Liddy, A.M., Ghoari, B., Hawkes, C., Enriquez, C.A., Gladstone, D.J., Manosalva Alzate, H.A., Khosravani, H., Hopyan, J.J., Sivakumar, K., Son, M., Boulos, M.I., Hamind, M.A., Swartz, R.H., Murphy, R., Reiter, S., Fitzpatrick, T., Bhandari, V., Good, J., Penn, M., Naylor, M., Frost, S., Cayley, A., Akthar, F., Williams, J., Kalman, L., Crellin, L., Wiegner, R., Singh, R.S., Stewart, T., To, W., Singh, S., Pikula, A., Jaigobin, C., Carpani, F., Silver, F., Janssen, H., Schaafsma, J., del Campo, M., Alskaini, M., Rajendram, P., Fairall, P., Granfield, B., Crawford, D., Jabs, J., White, L., Sivakumar, L., Piquette, L., Nguyen, T., Nomani, A., Wagner, A., Alrohimi, A., Butt, A., D'Souza, A., Gajurel, B., Vekhande, C., Kamble, H., Kalashyan, H., Lloret, M., Benguzzi, M., Arsalan, N., Ishaque, N., Ashayeriahmadabad, R., Samiento, R., Hosseini, S., Kazi, S., Das, S., Sugumar, T., Selchen, D., Kostyrko, P., Muccilli, A., Saposnik, A.G., Vandervelde, C., Ratnayake, K., McMillan, S., Katsanos, A., Shoamanesh, A., Sahlas, D.J., Naidoo, V., Todorov, V., Toma, H., Brar, J., Lee, J., Horton, M., Chen, S., Shand, E., Weatherby, S., Jin, A., Durafourt, B., Jalini, S., Gardner, A., Tyson, C., Junk, E., Foster, K., Bolt, K., Sylvain, N., Maley, S., Urroz, L., Peeling, L., Kelly, M., Whelan, R., Cooley, R., Teitelbaum, J., Boutayeb, A., Moore, A., Cole, E., Waxman, L., Ben-Amor, N., Sanchez, R., Khalil, S., Nehme, A., Legault, C., Tampieri, D., Ehrensperger, E., Vieira, L., Cortes, M., Angle, M., Hannouche, M., Badawy, M., Werner, K., Wieszmuellner, S., Langer, A., Gisold, A., Zach, H., Rommer, P., Macher, S., Blechinger, S., Marik, W., Series, W., Baumgartinger, M., Krebs, S., Koski, J., Eirola, S., Ivanoff, T., Erakanto, A., Kupari, L., Sibolt, G., Panula, J., Tomppo, L., Tiainen, M., Ahlstrom, M., Martinez Majander, N., Suomalainen, O., Raty, S., Levi, C., Kerr, E., Allen, J., Kaauwai, L.P., Belevski, L., Russell, M., Ormond, S., Chew, A., Loiselle, A., Royan, A., Hughes, B., Garcia Esperon, C., Pepper, E., Miteff, F., He, J., Lycett, M., Min, M., Murray, N., Pavey, N., Starling de Barros, R., Gangadharan, S., Dunkerton, S., Waller, S., Canento Sanchez, T., Wellings, T., Edmonds, G., Whittaker, K.A., Ewing, M., Lee, P., Singkang, R., McDonald, A., Dos Santos, A., Shin, C., Jackson, D., Tsoleridis, J., Fisicchia, L., Parsons, N., Shenoy, N., Smith, S., Sharobeam, A., Balabanski, A., Park, A., Williams, C., Pavlin-Premri, D., Rodrigues, E., Alemseged, F., Ng, F., Zhao, H., Beharry, J., Ng, J.L., Williamson, J., Wong, J.Z.W., Li, K., Kwan, M.K., Valente, M., Yassi, N., Cooley, R., Yogendrakumar, V., McNamara, B., Buchanan, C., McCarthy, C., Thomas, G., Stephens, K., Chung, M., Chung, M.F., Tang, M., Busch, T., Frost, T., Lee, R., Stuart, N., Pachani, N., Menon, A., Borojevic, B., Linton, C.M., Garcia, G., Callaly, E.P., Dewey, H., Liu, J., Chen, J., Wong, J., Nowak, K., To, K., Lizak, N.S., Bhalala, O., Park, P., Tan, P., Martins, R., Cody, R., Forbes, R., Chen, S.K., Ooi, S., Tu, S., Dang, Y.L., Ling, Z., Cranefield, J., Drew, R., Tan, A., Kurunawai, C., Harvey, J., Mahadevan, J.J., Cagi, L., Palanikumar, L., Chia, L.N., Goh, R., El-Masri, S., Urbi, B., Rapier, C., Berrill, H., McEvoy, H., Dunning, R., Kuriakose, S., Chad, T., Sapaen, V., Sabet, A., Shah, D., Yeow, D., Lilley, K., Ward, K., Mozhy Mahizhnan, M., Tan, M., Lynch, C., Coveney, S., Tobin, K., McCabe, J., Marnane, M., Murphy, S., Large, M., Moynihan, B., Boyle, K., Sanjuan, E., Sanchis, M., Boned, S., Pancorbo, O., Sala, V., Garcia, L., Garcia-Tornel, A., Juega, J., Pagola, J., Santana, K., Requena, M., Muchada, M., Olive, M., Lozano, P.J., Rubiera, M., Deck, M., Rodriguez, N., Gomez, B., Reyes Munoz, F.J., Gomez, A.S., Sanz, A.C., Garcia, E.C., Penacoba, G., Ramos, M.E., de Lera Alfonso, M., Feliu, A, Pardo, L., Ramirez, P., Murillo, A., Lopez Dominguez, D., Rodriguez, J., Terceno Izaga, M., Reina, M., Viturro, S.B., Bojaryn, U., Vera Monge, V.A., Silva Blas, Y., R Siew, R., Agustin, S J, Seet, C., Tianming, T., d'Emden, A., Murray, A., Welch, A., Hatherley, K., Day, N., Smith, W., MacRae, E., Mitchell, E.S., Mahmood, A., Elliot, J., Neilson, S., Biswas, V., Brown, C., Lewis, A., Ashton, A., Werring, D., Perry, R., Muhammad, R., Lee, Y.C., Black, A., Robinson, A., Williams, A., Banaras, A., Cahoy, C., Raingold, G., Marinescu, M., Atang, N., Bason, N., Francia, N., Obarey, S., Feerick, S., Joseph, J., Schulz, U., Irons, R., Benjamin, J., Quinn, L., Jhoots, 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Abstract

Individuals with minor ischaemic stroke and intracranial occlusion are at increased risk of poor outcomes. Intravenous thrombolysis with tenecteplase might improve outcomes in this population. We aimed to test the superiority of intravenous tenecteplase over non-thrombolytic standard of care in patients with minor ischaemic stroke and intracranial occlusion or focal perfusion abnormality.

Published
2024
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9. Concept of standard raw drug substitution in Traditional Siddha Medicine - A Review

Author

Vinayak S, Sivakumar L, Shree Devi M S, Vijayakumar, Sunil Kumar K N, Eugene Wilson, Aravind D, Shyamala Rajkumar, and K. Kanakavalli

Subjects
Siddha Medicine, Risk analysis (engineering), Computer science, Tamil, Substitution (logic), Siddha, language, Drug Substitution, language.human_language
Abstract

Classical Siddha medicine recommends the usage of functionally parallel substitute raw drugs in the scarcity of the original material. The concept of standard raw drug substitution is designated by the Tamil term Matru sarakku, which emphasizes selecting alternatives either in herbal or non-herbal sources based on certain attributes. Functionally similar materials are suggested for balancing the deficit based on such parameters. Literature sources from Siddha medicine and other allied subjects were explored and documented for the inclusive understanding of the concept of ideal substitution. Few of the standard substitutes mentioned in the classical Siddha literature were evaluated in a scientific account for its justification. An outlook on different specimens as described in the ancient texts of Tamil medicine indicates the usage of substitutes from numerous plants, animals, and other metallo-mineral ingredients. The rationale of selecting alternatives primarily depends on the equivalent following traditional attributes like organoleptic entities, potency, division, general properties, specific actions, and medicinal uses of the material shared between the raw drugs. This must undergo a systematic evaluation by pharmacognostic and phytochemical studies to justify current practices of substitution. A systematic document in these lines will give a proper guideline for the effective employment of substitute drugs in the current scenario of dwindling official botanical sources for many Traditional Siddha formulations.

Published
2021
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17. Artificial Neural Network Predictive Modelling of Laser Micro-Grooving for Commercial Pure Titanium (CP Ti) Grade 2.

Author

Sivaraos, Zuhair, A. K., Salleh, M. S., Ali, M. A. M., Kadirgama, Dubey, U. K., Pujari, Satish, and Sivakumar, L. D.

Subjects
ARTIFICIAL neural networks, LASER beam cutting, INDUSTRIAL electronics, MANUFACTURING processes, TITANIUM, WATER jet cutting, DENTAL metallurgy
Abstract

Grooving is the process of making a narrow channel on a surface of flat or cylindrical workpiece. Groove is precisely made to parts used in automotive, biomedical, and electronics industries. In automotive industries, groove plays an important role especially on mechanical parts to precisely locate seal (oring) to prevent gas/oil leakage between dynamic mating parts. On the other hand, artificial neural network (ANN) has been widely used in developing predictive models of various manufacturing processes to save huge amount of production time and money for industries. Unfortunately, very limited research has been investigated on micro groove quality employing ANN predictive models. Therefore, this research work presents on how the Artificial Neural Network (ANN) predictive model has been established, optimised and utilised to predict the laser micro-grooving quality of commercial pure titanium grade 2 material. A 3KW CO2 laser cutting machine was employed considering laser power, gas pressure, cutting speed, depth of cut and focal distance as the design parameters for modelling. On the other hand, three significant responses namely groove depth, groove width and groove corner radius were investigated. Experimental results were fed to establish the ANN predictive model, which then its parameters were optimized to gain high level prediction accuracy. The predicted results of ANN model presented the mean absolute percentage error for groove depth, groove width and groove corner radius at about 7.29%, 10.93% and 11.96% respectively. The obtained predictive results were found quite promising with the average of mean absolute percentage error (MAPE) for quality predictions which falls between 10 to 15%, concluding the validity of the developed ANN predictive model. [ABSTRACT FROM AUTHOR]

Published
2021

38. An Innovative Approach in Fault Diagnostics of Steam Turbine Performance Using ANN and M-SVM Algorithms.

Author

Devi, S. and Sivakumar, L.

Subjects
STEAM-turbines, ARTIFICIAL neural networks, ALGORITHMS, TURBINES
Abstract

In this study, an artificial neural network (ANN) and multi-support vector machine (M-SVM) models are developed to predict seven kinds of faults associated with turbine of thermal power plant. Information about changes with respect to base (design / performance guaranteed) values in seven key parameters/indices namely throttle flow, throttle pressure, first stage pressure, hot reheat pressure, cross-over pressure, HP efficiency and IP efficiency enable proper interpretation of different faults such as solid particle erosion (SPE) in HP turbine, IP turbine, deposits and peening in HP turbine, deposits and peening in IP turbine, deposits in IP turbine, rubs in IP turbine and deposits and damages in IP turbine. All the fault types are diagnosed based on observation of seven process parameters/ indices over a long time. The trends of changes - either increasing or decreasing direction -- with respect to base values are fed as inputs to the networks and their output identifies the type of fault. A comparison between the classifier models is discussed with the proposed action plan to improve the smooth running of the machines. [ABSTRACT FROM AUTHOR]

Published
2014

39. An Innovative Study and Binary Modeling of Thermal Power Plant Using Artificial Neural Network and Multiple Linear Regression.

Author

Devi, S., Sivakumar, L., and Saravanan, M.

Subjects
ARTIFICIAL neural networks, REGRESSION analysis, POWER plants, ERROR analysis in mathematics, STATISTICAL errors, STEAM power plants
Abstract

The article presents modeling of a 40 MW power plant using the observed onsite data using ANN and MLR models. The four different structures of neural networks are employed in two stages which are then integrated into a single ANN model representing a complete model of the thermal power plant. The method is further compared with the multiple linear regression (MLR) method and their detailed statistical error analysis showed that the ANN models present a very good accuracy with correlation coefficient of 0.999209 which makes these models fast in response and easy to be updated with new plant data. These measures clearly demonstrated the efficient prediction accuracy of the neural networks in modeling of the 40 MW power plants. [ABSTRACT FROM AUTHOR]

Published
2013

40. ANTIDEPRESSANT ACTIVITY OF POLYHERBAL EXTRACT ON RODENTS.

Author

Suresh, R., Selvan, A. Tamil, Johnson, D. Benito, Kumar, R. Suresh, Venkatanarayanan, R., and Sivakumar, L.

Subjects
HERBAL medicine, MENTAL depression, THERAPEUTICS, PLANT extracts, LABORATORY rats, CYCAS, SPIKENARD, ABSINTH wormwood, EXTRACTION (Chemistry)
Abstract

In this study, polyherbal extract of Cycas circinalis, Nardostachys jatamansi and Artemisia absinthium ethanolic fraction was explored for its antidepressant property using Forced swim test (FST) and Tail suspension test (TST). Many of its individual constituents have been used for central nervous system (CNS) activities but no systematic work was carried on this combination. In this study its effect on depression was explored in rats. For this purpose the plants part were extracted by successive solvent extraction by Soxhylation. Ethanolic extract was chosen for the pharmacological evaluation, based upon the phytochemical and instrumental analysis. The ethanolic extract was subjected to FT-IR analysis for finding the possible number and nature of function groups present in it. Also the extract was analysed by HPLC for the number possible phytocompounds/phytoconstituents present, which may directly or indirectly involve in the brain neurochemical activity. Acute and Subacute toxicity study revealed the dose upto 2000mg/kg the extract had not toxic symptoms and no mortality. The therapeutic dose was found to be 200mg/kg and there was no toxic damage to liver and kidney observed in subacute toxicity study. The ethanolic extract of the polyherbal combination exhibited significant (P<0.001) antidepressant activity as indicated by its ability to decrease swim stress and tail suspension induced immobility time in rats as compared with that standard Fluoxetine. As well as restoring biogenic amines to normal level that was altered by the swim stress and tail suspension test in whole rat brain assay by HPTLC method. The result indicates this polyherbal combination can be a potential candidate for .managing depression. However further studies are required to confirm the exact therapeutic efficacy. [ABSTRACT FROM AUTHOR]

Published
2013

41. Simplified approximations for the accumulation value and time constant for an evaporator system in drum-type boilers.

Author

Dharmalingam, S., Sivakumar, L., and Kumar, K. K. Anil

Subjects
EVAPORATORS, BOILERS, PRESSURE, COMBUSTION, STEAM
Abstract

The storage capacity of the evaporator system of a boiler helps in minimizing the steam pressure fluctuations during load changes even before the combustion control comes into play. The quantitative representation of the storage capacity is usually expressed as an index known as the accumulation value and it quantifies the steam that can be additionally drawn for unit pressure drop. Further, the time constant of the evaporator system can be calculated using the accumulation value. The time constants calculated for varying load clearly indicates non-linear behaviour of the evaporator system. The time constant forms the basis for designing suitable controllers. The simplified approximate relationships for the calculation of the accumulation value of the evaporator of a boiler as a function of drum operating pressure, and of the time constant as a function of varying load, are given for different ratings of the boiler. [ABSTRACT FROM AUTHOR]

Published
2010
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