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2. Application of an Efficient Bayesian Back Analysis Framework for Settlement Prediction of Soft Soils: A Case Study

Author

Huang, Shan, Huang, Jinsong, Kelly, Richard, Jones, Merrick, Kamruzzaman, A. H. M., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Lu, Xinzheng, Series Editor, Rujikiatkamjorn, Cholachat, editor, Xue, Jianfeng, editor, and Indraratna, Buddhima, editor

Published
2025
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7. Treatment Intensification With Either Fludarabine, AraC, G-CSF and Idarubicin, or Cladribine Plus Daunorubicin and AraC on the Basis of Residual Disease Status in Older Patients With AML: Results From the NCRI AML18 Trial

Author

Russell, Nigel H., Thomas, Abin, Hills, Robert K., Thomas, Ian, Gilkes, Amanda, Almuina, Nuria Marquez, Burns, Sarah, Marsh, Lucy, Vyas, Paresh, Metzner, Marlen, McCarthy, Nicholas, Andrew, Georgia, Byrne, Jennifer, Sellar, Rob S., Kelly, Richard, Cahalin, Paul, Overgaard, Ulrik Malthe, Mehta, Priyanka, Dennis, Mike, Knapper, Steven, and Freeman, Sylvie D.

Published
2024
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8. Factors Associated with Longitudinal Changes in Mammographic Density in a Multiethnic Breast Screening Cohort of Postmenopausal Women

Author

Park, Hannah Lui, Ziogas, Argyrios, Feig, Stephen A, Kirmizi, Roza Lorin, Lee, Christie Jiwon, Alvarez, Andrea, Lucia, Rachel McFarland, Goodman, Deborah, Larsen, Kathryn M, Kelly, Richard, and Anton-Culver, Hoda

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Aging, Clinical Research, Prevention, Women's Health, Cancer, Breast Cancer, Estrogen, Obesity, Nutrition, 2.3 Psychological, social and economic factors, Female, Humans, Middle Aged, Breast Density, Breast Neoplasms, Mammography, Postmenopause, Risk Factors, Estrogens, Psychology, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundBreast density is an important risk factor for breast cancer and is known to be associated with characteristics such as age, race, and hormone levels; however, it is unclear what factors contribute to changes in breast density in postmenopausal women over time. Understanding factors associated with density changes may enable a better understanding of breast cancer risk and facilitate potential strategies for prevention.MethodsThis study investigated potential associations between personal factors and changes in mammographic density in a cohort of 3,392 postmenopausal women with no personal history of breast cancer between 2011 and 2017. Self-reported information on demographics, breast and reproductive history, and lifestyle factors, including body mass index (BMI), alcohol intake, smoking, and physical activity, was collected by an electronic intake form, and breast imaging reporting and database system (BI-RADS) mammographic density scores were obtained from electronic medical records. Factors associated with a longitudinal increase or decrease in mammographic density were identified using Fisher's exact test and multivariate conditional logistic regression.Results7.9% of women exhibited a longitudinal decrease in mammographic density, 6.7% exhibited an increase, and 85.4% exhibited no change. Longitudinal changes in mammographic density were correlated with age, race/ethnicity, and age at menopause in the univariate analysis. In the multivariate analysis, Asian women were more likely to exhibit a longitudinal increase in mammographic density and less likely to exhibit a decrease compared to White women. On the other hand, obese women were less likely to exhibit an increase and more likely to exhibit a decrease compared to normal weight women. Women who underwent menopause at age 55 years or older were less likely to exhibit a decrease in mammographic density compared to women who underwent menopause at a younger age. Besides obesity, lifestyle factors (alcohol intake, smoking, and physical activity) were not associated with longitudinal changes in mammographic density.ConclusionsThe associations we observed between Asian race/obesity and longitudinal changes in BI-RADS density in postmenopausal women are paradoxical in that breast cancer risk is lower in Asian women and higher in obese women. However, the association between later age at menopause and a decreased likelihood of decreasing in BI-RADS density over time is consistent with later age at menopause being a risk factor for breast cancer and suggests a potential relationship between greater cumulative lifetime estrogen exposure and relative stability in breast density after menopause. Our findings support the complexity of the relationships between breast density, BMI, hormone exposure, and breast cancer risk.

Published
2023

9. A phase 1b study of venetoclax and alvocidib in patients with relapsed/refractory acute myeloid leukemia

Author

Jonas, Brian A, Hou, Jing‐Zhou, Roboz, Gail J, Alvares, Caroline L, Jeyakumar, Deepa, Edwards, John R, Erba, Harry P, Kelly, Richard J, Röllig, Christoph, Fiedler, Walter, Brackman, Deanna, Siddani, Satya R, Chyla, Brenda, Hilger‐Rolfe, Jacqueline, and Watts, Justin M

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Hematology, Clinical Research, Clinical Trials and Supportive Activities, Orphan Drug, Childhood Leukemia, Patient Safety, Pediatric Cancer, Pediatric, Rare Diseases, Cancer, 6.1 Pharmaceuticals, 6.2 Cellular and gene therapies, Good Health and Well Being, Humans, Antineoplastic Combined Chemotherapy Protocols, Bridged Bicyclo Compounds, Heterocyclic, Leukemia, Myeloid, Acute, acute myeloid leukemia, alvocidib, BCL-2, drug resistance, MCL-1, venetoclax, Cardiorespiratory Medicine and Haematology, Immunology, Cardiovascular medicine and haematology
Abstract

Relapsed/refractory (R/R) Acute Myeloid Leukemia (AML) is a genetically complex and heterogeneous disease with a poor prognosis and limited treatment options. Thus, there is an urgent need to develop therapeutic combinations to overcome drug resistance in AML. This open-label, multicenter, international, phase 1b study evaluated the safety, efficacy, and pharmacokinetics of venetoclax in combination with alvocidib in patients with R/R AML. Patients were treated with escalating doses of venetoclax (400, 600, and 800 mg QD, orally, days 1-28) and alvocidib (45 and 60 mg/m2 , intravenously, days 1-3) in 28-day cycles. The combination was found to be safe and tolerable, with no maximum tolerated dose reached. Drug-related Grade ≥3 adverse events were reported in 23 (65.7%) for venetoclax and 24 (68.6%) for alvocidib. No drug-related AEs were fatal. Gastrointestinal toxicities, including diarrhea, nausea, and vomiting were notable and frequent; otherwise, the toxicities reported were consistent with the safety profile of both agents. The response rate was modest (complete remission [CR] + incomplete CR [CRi], 11.4%; CR + CRi + partial response rate + morphologic leukemia-free state, 20%). There was no change in alvocidib pharmacokinetics with increasing doses of venetoclax. However, when venetoclax was administered with alvocidib, AUC24 and Cmax decreased by 18% and 19%, respectively. A recommended phase 2 dose was not established due to lack of meaningful increase in efficacy across all cohorts compared to what was previously observed with each agent alone. Future studies could consider the role of the sequence, dosing, and the use of a more selective MCL1 inhibitor for the R/R AML population.

Published
2023

10. Potential Use of AS 5104 for Reliability-Based Design

Author

Kelly, Richard, Beard, Kate, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Lu, Xinzheng, Series Editor, Khabbaz, Hadi, editor, Rujikiatkamjorn, Cholachat, editor, and Parsa-Pajouh, Ali, editor

Published
2024
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11. Tranexamic acid versus placebo to prevent bleeding in patients with haematological malignancies and severe thrombocytopenia (TREATT): a randomised, double-blind, parallel, phase 3 superiority trial

Author

Estcourt, Lise J, McQuilten, Zoe K, Bardy, Peter, Cole-Sinclair, Merrole, Collins, Graham P., Crispin, Philip J., Curnow, Elinor, Curnow, Jennifer, Degelia, Amber, Dyer, Claire, Friebe, Adam, Floro, Lajos, Grand, Effie, Hudson, Cara, Jones, Gail, Joseph, Joanne, Kallmeyer, Charlotte, Karakantza, Marina, Kerr, Paul, Last, Sara, Lobo-Clarke, Maria, Lumley, Matthew, McMullin, Mary F, Medd, Patrick G., Morton, Suzy M., Mumford, Andrew D., Mushkbar, Maria, Parsons, Joseph, Powter, Gillian, Sekhar, Mallika, Smith, Laura, Soutar, Richard, Stevenson, William S., Subramoniapillai, Elango, Szer, Jeff, Thomas, Helen, Waters, Neil A., Wei, Andrew H., Westerman, David A., Wexler, Sarah A., Wood, Erica M., Stanworth, Simon J., Abioye, Adrienne, Afghan, Rabia, Ai, Sylvia Ai, Akanni, Magbor, Alajangi, Rajesh, Alam, Usmaan, Al-Bubseeree, Bahaa, Alderson, Sophie, Alderson, Craig, Ali, Sayed, Ali, Kabir, Alighan, Rookmeen, Allam, Rebecca Allam, Allen, Tania, Al-Sakkaf, Wesam, Ames, Kate, Anderson, Jacqueline, Andrews, Colin, Angel, Ann-Marie, Anlya, Manuela Anlya, Ansari, Farah, Appleby, Rowan, Arnold, Claire, Asbjornsdottir, Hulda, Asfaw, Biruk, Atkins, Elissa, Atkinson, Leela, Aubrey, Clare, Ayesha, Noor, Babbola, Lola, Badcock, David, Badcock, Samuel, Baggio, Diva, Bailiff, Ben, Baines, Kizzy, Baker, Holly, Baker, Victoria, Ball, Lindsay, Ball, Martin, Balquin, Irwin, Banks, Emma, Banos, George, Barnett, Jaytee, Barrie, Claire, Barron, Claire, Barton, Rebecca, Bason, Nina, Batta, Bindu, Bautista, Dianne, Bayley, Angela, Bayly, Emma, Baynes, Fionnuala, Bazargan, Ali, Bazeley, Rachel, Beadle, Yvonne, Beardsmore, Claire, Beattie, Kate, Bedford, Caroline, Behal, Rachna, Behan, Daniel, Bejan, Lilihna, Bell, Sarah, Bell, Karen, Bell, Louise, Bell, Kaitlyn, Benjamin, Reuben, Bennett, Sam, Benson, Gary, Benson, Warwick, Bent, Cameron, Bergin, Krystal, Berry, Alex, Besenyei, Stephanie, Besley, Caroline, Betteridge, Scott, Beveridge, Leigh, Bhattacharyya, Abir, Billen, Annelies, Bilmon, Ian, Binns, Emma, Birt, Mark, Bishop, David, Blanco, Andrea, Bleby, Lisa, Blemnerhet, Richard, Blombery, Piers, Blyth, Emily, Blythe, Nicola, Boal, Lauren, Boden, Ali, Bokhari, Syed W.I., Bongetti, Elisa, Booth, Stephen, Borley, Jayne, Bowen, David, Bowers, Dawn, Boyd, Stephen, Bradley, Sarah, Bradman, Helen, Bretag, Peta, Brillante, Maria, Brockbank, Rachel, Brough, Yasmin, Brown, Ellen, Brown, Jo, Brown, Eleanor, Brown, Claire, Brown, Jenny, Brown, Susan, Browning, Joe, Brownsdon, Alex, Bruce, David, Brydon-Hill, Ruth, Buckwell, Andrea, Burgess, Dannielle, Burke, Glenda, Burley, Kate, Burney, Claire, Burns, David, Burrows, Samuel, burton, Kieran, Butler, Jason, Cambalova, Lenka, Camozzi, Maria C., Campbell, Philip, Campfield, Karen, Campion, Victoria, Cargo, Catherine, Carmona, Julia, Carney, Dennis, Casan, Joshua, Cashman, Helen, Catt, Lorraine, Cattell, Michael, Cavill, Megan, Chadbone, Rachel, Chaganti, Sridhar, Chai, Yee, Chai, Khai Li, Chang, Joshua, Chapman, Judith, Chapman, Oliver G., Chapter, Tamika, Charlton, Andrew, Chau, Celina, Chauhan, Saleena, Chavda, Nikesh, Chen, Frederick, Chen, Melody, Chen, Meng Xi, Chen, Melanie, Chen, Melissa, Cheok, Kathleen, Cheung, Mai, Chidgey, Luke, Chmielokliec, Karolina, Choi, Philip, Choi, Jae, Chok, Anne, Chopra, Ruchika, Christopherson, Louise, Chu, Vicky, Chua, Chong Chyn, Chudakou, Pavel, Chugh, Vidushi, Chung, Chi, Clark, Erin, Clarke, Peter, Clarke, Kathleen, Clay, Jennifer, Clayton, Laura, Clements, Mitch, Clemmens, Jonathan, Clifford, Ruth, Collett, Dave, Collins, Maia, Collyer, Emily, Connolly, Maureen, Cook, Mark, Coombs, Sarah, Coppell, Jason, Cornwell, Sophie, Corrigan, Claire, Coughlin, Elizabeth, Couling, Jennifer, Cousins, Tony, Cowan, Catriona, Cox, Christine, Cox, Catherine, Coyle, Luke, Craig, Emily, Creasey, Thomas, Croan, Laura, Croft, Jane, Crosbie, Nicola, Crowe, Josephine, Crowther, Helen, Crozier, Jane, Culleton, Naomi, Cullis, Jonathan, Cumming, Anita, Cummins, Michelle, Cunningham, Adam, Curley, Cameron, Curtis, Samantha, Cuthbert, Robert, Cuthill, Kirsty, Dahahayake, Dinusha A, Dang, Amy, Davies, Marc, Davies, Ceri, Dawson, Emily, Day, Tom, De Abrew, Kanchana, De Lavallade, Hugues, De Silva, Neelaskshi, Dean, Georgina, Deane, Christopher, Demosthenous, Lisa, Desai, Amisha, Desborough, Michael, Devanny, Ian, Dhanapal, Jay, Dhani, Sundip, Di Martino, Vicky, Dickens, Emmy, DiCorleto, Carmen, Dinnett, Louise, Dirisan, Divya, Dixon, Karen, Dixon, Kiri, Doal, Inderjit, Dobivh, J, Docanto, Maria, Doecke, Helve, Donaldson, David, Donaldson, Kylee, Donohoe, Carrie, Douglas, Ashley, Doung, Stephen, Downer, Susan, D'Rozario, James, Drummond, Malcolm, Drummond, Mark, Drummond, Samantha, Drysdale, Elizabeth, D'Souza, Ross, D'Souza, Eugene, Dunn, Alex, Dutton, David, Dyson, Martin, Ediriwicurena, Kushani, Edleston, Sharon, Edwards, Dawn, Edwards, Morgan, Edwards, Anita, Eise, Nicole, Ellis, Steven, Ellis, Hayley, Elmonley, Shareef, Enstone, Rosemarie, Eordogh, Agnes, Erb, Sharon, Evans, Shannon, Evans, Megan, Ewing, Joanne, Eyre, Toby, Facey, Adam, Fammy, Mina, Farman, Jon, Farnell, Rachel, Favero, Laura, Fay, Keith, Ferguson, Karen, Fernon, Laura, Filshie, Robin, Finnegan, Damian, Fisher, Lisa, Flanagan, Asia, Fleck, Emma, Fletcher, Simon, Flora, Harpreet, Flower, Catherine, Fodor, Ioana, Foley, Heather, Folland, Emma, Folorunso, Comfort, Forbes, Molly, Fordwor, Katrina, Foster, Polly, Fox, Vanessa, Fox, Thomas, Francis, Olesya, Fryearson, Louise, Fuery, Madonna, Fung, Jiin, Furtado, Michelle, Galloway-Browne, Leanne, Gamble, Louise, Gamgee, Jeanette, Ganapathy, Arundathi, Gardner, Hayley, Gardner, Clare, Gasmelsheed, Noha, Gately, Amy, Gaynor, Lynda, Gebreid, Alex, Geffens, Ruth, George, Rachel, Gertner, Aniko, Ghebeh, Manar, Ghirardini, Emanuela, Giddings, Melainie, Gillett, Sandra, Gillett, Karen, Giri, Pratyush, Glass, Chris, Glewis, Sarah, Gooding, Sarah, Gordon, Olivia, Gordon, Joanne, Gottlieb, David, Gowda, Koushik, Gower, Elysie, Gray, Nicola, Grayer, Jo, Greaves, Elaine, Greenaway, Sally Anne, Greenfield, Graeme, Greenwood, Matthew, Gregory, Gareth, Griffin, James, Griffith, Julia, Griffith, James, Griffiths, Lindsey, Grzegrzolka, Paulina, Gu, Yisu, Guest, Jo, Guinai, Rosanna, Gullapalli, Veena, Gunolr, A., Guo, Lina, H, Wayne, Hagua, Sophia, Haile, Senait, Hall, Richard, Hamdollah-Zadeh, Maryam, Hanif, Zahra, Hanlon, Kathleen, Hann, Nicholas, Hanna, Ramez, Hannah, Guy, Hapuarachchi, Sameera, Hardman, Jacinta, Hardy, Alison, Harris, Anthony, Harris, Kylie, Harrison, Beth, Harrison, Simon, Harrison, Lea-Anne, Harrop, Sean, Harvey, Caroline, Hatcliffe, Faye, Hawking, Jo, Hawkins, Matthew, Hayden, Janet, Hayman, Michelle, Haynes, Elizabeth, Heaney, Nicholas, Hebbard, Andrew, Hempton, Jenny, Hendunneti, Sasanka, Henry, Maeve, Heywood, Jonathan, Hildyard, Catherine, Hill, Lydia, Hilldrith, Annette, Hitev, Petar, Hiwase, Smita, Hiwase, Devendra, Hoare, Chris, Hodge, Renate, Holloway, Amy, Holt, Chloe, Holton, Kelly, Homer, Lauren, Horne, Gillian, Horvath, Noemi, Hotong, Linda, Houdyk, Kristen, Houseman, Katy, Hoxhallari, Ilda, Hsu, Hannah, Hsu, Nina, Huang, Gillian, Hudson, Kerryn, Hufton, Melanie, Hughes, Timothy, Hughes, Siobhan, Hurley, Kate, Huxley, Rosie, Ibitoye, Temitope, Ibrouf, Abubaken, Inam, Farha, Indran, Tishya, Ingham, Karen, Innes, Calum, Irvine, David, Jaafar, Sarah, Jain, Manish, Jameson, Laura, Janjua, Pardeep, Jarvis, Rebecca, Jatheendran, Abirami, Javed, Abbie, Jen, Sheila, Jobanpura, Shailesh, Jobson, Irene, John, Deborah, Johns, Sophie, Johnston, Amanda, Jones, Hollie, Jones, Francesca, Joniak, Karolina, Jovanovic, Michael, Jovic, Anita, Joyce, Lauren, Judd, Andrew, Kakarlamudi, Sudhakar, Kakaroubas, Nick, Kalita, Maggie, Kam, Shirly, Kan, Julie, Kandle, P, Kanellopoulos, Alex, Kao, Chien, Kaparou, Maria, Kartsios, Charamlampos, Katsioulas, Vicki, Kaye, Russell, Keen, Katie, Kelly, Richard, Kelly, Pauline, Kelly, Donna, Kelly, Melanie, Kennedy, Glen, Kennedy, Nola, Kenny, Angela, Kenworthy, Zoe, Kerridge, Ian, Kesavan, Murali, Khafizi, Angelika, Khakwani, Muhammad, Khalid, Amna, Khamly, Kate, Khan, Anjum, Khan, Dalia, Khan, Mojid, Khan, Lubna, Khoo, Mona, Khwaja, Asim, Kim, Grace, King, Andrew, King, Vicky, King, Donna, Kinsella, Francesca, Kipp, David, Kirandeep, Pachoo, Kirui, Laura C., Kishore, Bhuvan, Knectlhi, Christopher, Knot, Amy, Knot, Armit, Ko, Cathy, Kolaric, Caitlin, Koo, Ray, Kotadia, Mary, Kothari, Jaimal, Kottaridis, Panagiotis D., Kuiluinathan, Gajan, Kulasekararaj, Austin, Kwan, John, Kwok, Marwan, Kwok, Phillip, Kwok, Fiona, Laane, Kristiina, Lad, Deena, Laird, Jennifer, Lam, Ada, Lane, Mary, Lanenco, Monica, Lang, Susan, Langridge, Alex, Langton, Catherine, Lannon, Michelle, Latif, Annie, Latimer, Maya, Latter, Ruth, Lau, I-Jun, Lawless, Sarah, Lawless, Theresa, Leach, Mike, Leaney, Sarah, Leary, Heather, Leavy, James, LeBlanc, Abbey, Lee, Vivienne, Lee, Edwin, Lee, Jenny, Lee, Tamara, Leischkie, Marian, Leitinger, Emma, Leon, Christopher, Leonard, Jayne, Lewis, David, Lewis, Ian, Lewis, Tania, Lim, Daniel, Littlewood, Kelly, Liu, Dara, Loh, Joanna, Lokare, Anand, Lomas, Oliver, Lovell, Richard, Lowe, Theresa, Lowry, Lisa, Lubowiecki, Marcin, Lumb, Rebecca, Lynch, Gail, Macaulay, Amanda, MacDonald, Lyndsey, MacDonald-Burn, Jill, Macmillan, Margaret, Maddock, Karen, Mahaliyana, Tomas, Mahon, Cassandra, Maidment, Alison, Maier, Susie, Mairos, Michelle, Majid, Mahseeman, Mak, Ka L, Mak, Anne, Malendrayogau, Arunthrthy, Malham, Hana, Malyon, Felicity, Mandadapu, Vineela, Mandel, Laura, Mant, Sarah, Manton, Ruth, Maouche, Nadjoua, Maqbool, Muhammad G., Marchant, Gregory, Marinho, Mariana, Marks, David, Marner, Mike, Marr, Helen, Marshall, Gillian, Martin, Siobhan, Martin, Abigail, Marzolini, Maria, Mason, Kiara, Massie, Jonathan, Masson, Rebecca, Mathavan, Vidya, Mathew, Siju, Mathie, Judith, Mattocks, Lehenta, Maybury, Bernard, Mayer, Georgina, McAlister, Chyrelle, McAllister, Jo, McConnell, Stewart, McCracken, James, McCullagh, Liz, McCulloch, Rory, Mcdermott, Christopher, Mcdonald, Kerian, McGinniss, Laura, McGurk, Fiona, McIlwain, Jessica, McIver, Kirsten, Mckay, Pam, McKenna, Lorraine, Mclornan, Donal, McMahon, Coalon, McNeice, Linda, McNeill, Susan, McNickle, Molly, McQueen, Fiona, McRae, Simon, McTaggart, Bobby, Mehew, Jenny, Mehra, Varnn, Melly, Michelle, Menichelli, Tara, Micklethwatte, Ken, Mihailescue, Loredana, Mijovic, Aleksander, Millband, Hannah, Miller, Lucy, Millien, Samuel T., Milnthorpe, James, Minson, Adrian, Molnar, Eva, Monsour, Marc, Moody, Mary, Moon, Rebecca, Moore, Sally, Moore, Katy, Morgan, Kelly, Morralley, Rebecca, Morris, Denise, Morris, Kirk, Morrison, Nicole, Moss, Merinda, Mughal, Muhammad, Muir, Paul, Mukkath, David, Mulla, Aasiyu, Mulligan, Stephen, Mullings, Joanne, Mulqueen, Angela, Muluey, Caitlin, Murdoch, Sarah, Murrani, Sura, Murthy, Vidhya, Musngi, Jimmy, Mustafa, Nadreen, Mynes, Tracey, Nalpantidis, Anastasios, Nandurkar, Harshal, Nardone, Linda, Nasari, Latifa, Nash, Monica, Naylor, Georgina, Ngu, Loretta, Nguethina, Melissa, Nguyen, John, Nguyen, Joseph, Nichol, Wendy, Nicholls, Emma, Nicole, Catherine S., Nicolson, Phillip, Nielson, David, Nikolousis, Emmanouil, Nix, Georgina, Njoku, Rita, Norman, Jane, Norman, Amy, Norris, Phoebe, North, Daniel, Norwood, Megan, Notcheva, Gaynor, Novitzky-Basso, Igor, Nyaboko, Joseph, Nygren, Maria, Obu, Ingrid, O'Connell, Siobhan, O'Connor, Jody, O'Kelly, Deanna, O'Niell, Aideen, Ony, Jeremy, Oo, Kathy, Oo, April, Oppermann, Anne, Orr, Ruth, O'Sullivan, Mary, Page, Jennifer, Palfreyman, Emma, Paneesha, Shankaranarayana, Panicker, Shyam, Parbutt, Catherine, Parigi, Elesha, Paris, Gemma, Parker, Tracey, Parnell, Caroline, Parrish, Christopher, Parsons, Alex, Pasat, Mioara, Patel, Natasha, Patel, Vijay, Patel, Pooja, Patel, Chaya, Pati, Nalini, Patterson, Andrea, Paul, Lauren, Payet, Danielle, Payne, Elspeth, Peachey, Victoria, Pearson, Amanda, Peniket, Andy, Percy, Laura, Pereyra, Millicent, Pervaiz, Omer, Phalod, Gunjan D, Pham, Anh, Pho, Jason, Pickard, Keir, Pidcock, Michael, Piggin, Anna, Pishyar, Yalda, Pocock, Abigail, Pol, Ranjendres, Polzella, Paolo, Poolan, Sonia, Portingale, Vicki, Posnett, Claire, Potluri, Sandeep, Potter, Victoria, Pratt, Guy, Prodger, Catherine, Pueblo, Andres, Puliyayil, Anish, Puvanakumar, Pratheepan, Qadri, Abdul, Quach, Hang, Quinn, Michael, Rafferty, Mark, Rahman, Marzia, Raj, Kavita, Raj, Sonia, Rajendran, Ramina, Ramanan, Radha, Ramasamy, Karthik, Rampotas, Alexandros, Ranchhod, Natasha, Rashid, Sabia, Ratanjee, Sunita, Rathore, Gurpreet, Ratnasingam, Sumita, Rayat, Manjit, Rayner, Michael, Reddell-Denton, Rebecca, Redding, Nicola, Reddy, Udaya, Rehman, Atique, Rice, Carol, Riches, Iwona, Rider, Thomas, Riley, John, Rinaldi, Ciro, Roberts, Kayleigh, Roberts, Andrew, Robertson, Bryony, Robertson, Peter, Robinson, Dan, Robinson, Rebecca, Robjohns, Emma, Robledo, Laura, Rodrigues, Ana, Rofe, Chris, Roff, Bridie, Rogers, Rachel, Rolt, Jill, Rooney, Carmela, Rose, Kathy, Rose, Hannah, Ross, David, Rouf, Shahara, Rourke, Claire, Routledge, David, Ruggiero, Janet, Rule, Simon, Rumsey, Richard, Sagge, Cherry, Saldhana, Helen, Salisbury, Richard, Salisbury, Sarah, Salvaris, Ross, Sanders, Kay, Sangombe, Mirriam, Sanigorska, Anna, Santos, Kristine, Sarkis, Taylah, Sarma, Anita, Saunders, Natalie, Schmidt, Kara, Schmidtmann, Anja, Schumacher, Ann, Scorer, Tom Scorer, Scott, Asleigh, Seath, Ingrid, Sejman, Frances, Selim, Adrian, Shamim, Nadia, Shan, Jocelyn, Shanmuganathan, Naranie, Shanmugaranjan, Shaminie, Sharpe, Michelle, Sharpley, Faye, Shaw, Emma, Sheath, Cara, Sheehy, Oonagh, Shen, Vivian, Sherbide, Solomon, Sheridan, Mathew, Sheridan, Jane, Sheridon, Matthew, Shields, Tracy, Sim, Hau V, Sim, Shirlene, Sims, Matt, Singaraveloo, Lydia, Singh, Gurcharan, Singh, Jasmine, Sladesal, Shree, Sloan, Andrew, Slobodian, Peter, Smith, Sophie, Smith, Sarit, Smith, Claire, Smith, Alastair, Smith, Neil, Snowden, Katherine, Solis, Joel, Somios, Denise, Soo, Jade, Spanevello, Michelle, Spaulding, Madeleie, Spence, Laura, Spillane, Liz, Spiteri, Alisha, Sprigg, Naomi, Springett, Sally, Stafford, Lynn, Stainthorp, Katherine, Stark, Kate, Steeden, Louise, Stephen, Ella, Stephenson, Aisling, Stewart, Andrew, Stewart, Orla, Stobie, Emma, Stokes, Chelsea, Streater, Jacqui, Suddens, Charlie-Marie, Suntharalingam, Surenthini, Surana, Narinder, Sutherland, Robyn, Sutherland, Antony, Sutton, David, Sweeney, Connor, Sweet, Reilly, Szucs, Aniko P, Taheri, Leila E., Tailor, Hinesh, Tam, Constantine, Tambakis, George, Tamplin, Mary, Tan, Chee, Tan, Sui, Tan, Joanne, Tan, Zhi, Taran, Tatiana, Tarpey, Fiona, Taseka, Angela, Tasker, Suzy, Tatarczuch, Maciej, Tayabali, Sarrah, Taylor, Hannah, Taylor, Robert, Taylor, Melaine, Taylor-Moore, Ella, Teasdale, Lesley, Tebbet, Elizabeth, Tedjasepstra, Aditya, Tedjaseputra, Aditya, Tepkumkun, Oummy, Terpstra, Andrew, Thomas, Wayne, Thomas, Shanice, Thompson, Rachel, Thornton, Thomas, Thorp, Bronwyn, Thrift, Moi Yap, Thwaites, Phillipa, Timbres, Jasmine, Tindall, Lauren, Tiong, Ing Soo, Tippler, Nicole, Todd, Tony, Todd, Shirley, Toghill, Neil, Tomlinson, Eve, Tooth, Jacinta, Topp, M., Trail, Nicola, Tran, Nguyen, Tran, Elizabeth, Tran, Vi, Treder, Bona, Tribbeck, Michelle, Trochowski, Siobhan, Truslove, Maria, Tse, Tsun, Tseu, Bing, Tucker, David, Turner, Kelly, Turner, Dianne, Turner, Herleen, Turner, Gillian, Twohig, Julie, Tylee, Thomas, Uhe, Micheleine, Underhill, Lauren, V, Joanne, Van der Vliet, Georgina, Van Tonder, Tina, VanderWeyden, Carrie, Varghese, Jerry, Vaughan, Lachlan, Veale, David, Vickaryyous, Nicky, Vince, Kathryn, Von Welligh, Jacoba, Vora, Sona, Wadehra, Karan, Walker, Rebecca, Walker, Stephen, Wallace, Roslyn, Wallniosve, Stephanie, Wallwork, S., Walmsley, Zoe, Walters, Fiona, Wang, Joyce, Wang, Angela, Wang, Chen, Wanyika, Mercy, Warcel, Dana, Wardrobe, Katrina, Warnes, Kristian, Waterhouse, Christopher, Waterworth, Adam, Watson, Caroline, Watson, Edmund, Watts, Emily, Weaver, Emma, Weber, Nicholas, Webley, Kaytie, Welford, Anna, Wells, Matt, Westbury, Sarah, Westcott, Jackie, Western, Robyn, Weston, Julia, White, Jessica, White, Phillipa, Whitehead, Anna, Whitehouse, James, Wieringa, Samantha, Willan, John, Williams, Sandra, Williams, Bethany, Williamson, Stephanie, Willoughby, Brett, Wilmot, Gail, Wilmott, Rosalind, Wilson, Joanna, Wilson, Emma, Wilson, Suzy, Wilson, Heather, Wilson, Caroline, Wilson, Tanya, Wilton, Margaret, Wiltshire, Paula, Wincup, Joanne, Wolf, Julia, Wong, Henna, Wong, Cyndi, Wong, Daniel, Wong, Jonathan, Wong, Shi Qin, Wood, Sarah, Wood, Henry, Wooding, Jackie, Woolley, Kelly, Wright, Myles, Wynn-Williams, Roland, Yannakou, Costas, Yeoh, Zhi Han, Yeung, David, Young, Agnes, Yuen, Flora, Yuen, Agnes, Zaja, Oliver, Zhang, Xiao-Yin, and Zhang, Mei

Published
2025
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12. Base and station regionalization

Author

Kelly, Richard L., LtGen and O'Connor, Michael J., CAPT

Subjects
MILITARY BASES, AMERICAN, WAR ON TERRORISM, 2001-, ROLES AND MISSIONS - Marine Corps - United States - Organization
Abstract

chart por

Published
2005

13. Contributions of Ted Kuwana to Analytical Sciences Education

Author

Wenzel, Thomas J, Kelly, Richard S, Larive, Cynthia K, and Gross, Erin M

Subjects
ASDL, analytical sciences digital library, education, teaching, active learning, Analytical Chemistry, Physical Chemistry (incl. Structural), Other Chemical Sciences
Published
2022

15. Excellence in warfighting support

Author

Kelly, Richard L., LtGen and Clifton, David R.

Subjects
LOGISTICS - Marine Corps - United States, FINANCE - Marine Corps - United States, APPROPRIATIONS AND EXPENDITURES - Marine Corps - United States
Abstract

chart

Published
2004

17. Fen li

Author

Kelly, Richard

Published
2013

33. The CAFC Backs The FTC View On Listing Device Patents In The Orange Book

Author

Kelly, Richard D.

Subjects
United States. Court of Appeals for the Federal Circuit -- Powers and duties, Medical equipment -- Cases -- Intellectual property -- Laws, regulations and rules, Physiological apparatus -- Cases -- Intellectual property -- Laws, regulations and rules, Patent infringement -- Cases, Pharmaceutical industry -- Cases -- Intellectual property, Company legal issue, Government regulation, Business, international
Abstract

On December 20 the Federal Circuit in Teva Branded Pharmaceutical Products R&D, Inc. (Teva) v. Amneal Pharmaceuticals (Amneal) affirmed the district court's decision that medical devices were not listable in [...]

Published
2025

38. Finally, An ODP Decision In Favor Of The Patentee

Author

Kelly, Richard D.

Subjects
Patentability -- Cases, Judicial opinions -- Cases, Pharmaceutical industry -- Intellectual property -- Cases, Company legal issue, Business, international
Abstract

In Allergan USA, Inc v Sun Pharmaceutical Indus. Ltd, Appeal No. 2024-1061, August 13, 2024, the Federal Circuit reversed the district court's holding that Allergan patent, U.S.P. 7,741,356 ('356) was [...]

Published
2024

39. Effects of environmental perturbation during the Late Triassic on the taxic diversity of British insects

Author

Kelly, Richard and Benton, Mike

Subjects
550
Abstract

The Late Triassic is a time of interest for investigating past periods of environmental perturbation as it experienced one of the most devasting extinction events in Earth history, the end Triassic extinction. Examining such past events is useful for understanding the broad patterns of ecosystem dynamics and how they respond to environmental change through time. Insects are incredibly diverse and integral to almost all terrestrial ecosystems. Therefore, understanding the dynamics of insect diversity and ecology through time provides insights into the processes that shape terrestrial ecosystems. A dataset of insect occurrence through the Triassic/Jurassic boundary (TJB) was compiled to analyse diversity dynamics and detect an extinction signal. Most insects from the Rhaetian/Hettangian were collected from the Severn Valley in Southwest England. From an initial assessment two main issues were found, namely, a lack of current discussion on the age of the insect-bearing deposits and the poor taxonomic state of the insects. Through stratigraphic revision, a series of insect-bearing horizons was established through the TJB. Then, the ~4000 British insect fossils were identified, dubious historical taxonomy was revised (nine species removed as nomen dubia), and newly discovered taxa were described (one new family, six new genera, and 16 new species). The compositions of the Rhaetian-Sinemurian assemblages were assessed in terms of species- and genus-level diversity and ecology. The results suggest that these assemblages are indeed distinct and do record a dramatic disruption to insect diversity in the Hettangian. However, the UK data are too patchy to establish long-term trends, so they were included in a dataset of all insects from the Late Triassic/Early Jurassic from the Palaeobiology Database. Through a series of analyses at a range of geographic, stratigraphic, and taxonomic levels compelling evidence was found for a dramatic decline in insect diversity at both local and global scales.

Published
2019

40. Impact of the Quick-Response Code Based In-Class Assignments on Student Engagement and Retention

Author

Goulding, Richard R. J., Harlick, Anna Maria, Kelly, Richard, and Oksanen, Karoliina

Abstract

The paper describes a teaching technique alternative to online-based student response systems. We explore the potential of quick response (QR) code sheets as a tool for formative assessment, feedback, as well as a way to increase class engagement, student participation, information retention, and as a method to develop communication skills. The technique is neither institution nor course bound and can be implemented in classes of numerous sizes and levels. While it resembles more traditional teaching methods than computerized student response systems, it is student centered and accommodates digital natives' approach to information gathering.

Published
2017

41. Effects of Menopause and High Fat Diet on Metabolic Outcomes in a Mouse Model of Alzheimer's Disease.

Author

Abi-Ghanem, Charly, Salinero, Abigail E., Smith, Rachel M., Kelly, Richard D., Belanger, Kasey M., Richard, Riane N., Paul, Aaron S., Herzog, Ava A., Thrasher, Christina A., Rybka, Krystyna A., Riccio, David, Gannon, Olivia J., Kordit, David, Kyaw, Nyi-Rein, Mansour, Febronia M., Groom, Emily, Brooks, Heddwen L., Robison, Lisa S., Pumiglia, Kevin, and Zuloaga, Damian G.

Subjects
HIGH-fat diet, ANIMAL models for aging, GLUCOSE metabolism disorders, ALZHEIMER'S disease, GLUCOSE intolerance
Abstract

Background: About two-thirds of those with Alzheimer's disease (AD) are women, most of whom are post-menopausal. Menopause accelerates dementia risk by increasing the risk for metabolic, cardiovascular, and cerebrovascular diseases. Mid-life metabolic disease (obesity, diabetes/prediabetes) is a well-known risk factor for dementia. A high fat diet can lead to poor metabolic health in both humans and rodents. Objective: Our goal was to determine the effects of a high fat diet on metabolic outcomes in the AppNL-F knock-in mouse model of AD and assess the effects of menopause. Methods: First, 3-month-old AppNL-F and WT female mice were placed on either a control or a high fat diet until 10 months of age then assessed for metabolic outcomes. Next, we did a more extensive assessment in AppNL-F mice that were administered VCD (4-vinylcyclohexene diepoxide) or vehicle (oil) and placed on a control or high fat diet for 7 months. VCD was used to model menopause by causing accelerated ovarian failure. Results: Compared to WT controls, AD female mice had worse glucose intolerance. Menopause led to metabolic impairment (weight gain and glucose intolerance) and further exacerbated obesity in response to a high fat diet. There were interactions between diet and menopause on some metabolic health serum biomarkers and the expression of hypothalamic markers related to energy balance. Conclusions: This work highlights the need to model endocrine aging in animal models of dementia and will contribute to further understanding the interaction between menopause and metabolic health in the context of AD. [ABSTRACT FROM AUTHOR]

Published
2024
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42. Addition of four doses of rituximab to standard induction chemotherapy in adult patients with precursor B-cell acute lymphoblastic leukaemia (UKALL14): a phase 3, multicentre, randomised controlled trial

Author

Marks, David I, Kirkwood, Amy A, Rowntree, Clare J, Aguiar, Melanie, Bailey, Katharine E, Beaton, Brendan, Cahalin, Paul, Castleton, Anna Z, Clifton-Hadley, Laura, Copland, Mhairi, Goldstone, Anthony H, Kelly, Richard, Lawrie, Emma, Lee, SooWah, McMillan, Andrew K, McMullin, Mary Frances, Menne, Tobias F, Mitchell, Rachel J, Moorman, Anthony V, Patel, Bela, Patrick, Pip, Smith, Paul, Taussig, David, Yallop, Deborah, Alapi, Krisztina Zuborne, and Fielding, Adele K

Published
2022
Full Text
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45. Muon catalyzed fusion : an investigation of reactor design

Author

Kelly, Richard and Rose, Steven

Subjects
530
Abstract

In this dissertation, we calculate the power capacity and tritium replacement ratios for muon catalyzed fusion vessels containing mixtures of deuterium and tritium (dt). This calculation is done for various wall thicknesses, types of metal and dt densities. This allows us to ascertain which of these configurations (wall thickness, metal and dt density) has the most promise. In order to calculate these quantities, we start with an assumed wall thickness and metal type and determine the muon energy necessary to penetrate the wall and emerge in the dt mixture. From the energy of the emerging muon we determine the vessel size for the different dt densities. For each vessel configuration we find a) the relationship between the steady state dt temperature, the vessel wall temperature and the muon flux; b) the maximum pressure the vessel can contain and c) the number of tritons bred per fusion neutron. Using the equation of state for the dt, we relate this maximum pressure to a maximum dt temperature from which we infer a maximum muon flux. Assuming 150 fusion reactions catalyzed per muon, we can then extract the power generated for each configuration and assess the ratio of the rates of tritium creation to tritium decay.

Published
2018
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47. Derivatives 2024

Author

Kelly, Richard

Subjects
Derivatives (Financial instruments) -- Laws, regulations and rules, Securities law -- Interpretation and construction, Government regulation, Business, international
Abstract

1. Documentation and Formalities 1.1 Please provide an overview of the documentation (or framework of documentation) on which derivatives transactions are typically entered into in your jurisdiction. Please note whether [...]

Published
2024

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