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8,898 results on '"A. ac"'

1. Clinical and Cardiometabolic Effects of Reducing Sedentary Behavior in Postmenopausal Women with Rheumatoid Arthritis

Author: Pinto, AJ, Meireles, K, Peçanha, T, Mazzolani, BC, Smaira, FI, Rezende, D, Benatti, FB, de Medeiros Ribeiro, AC, de Sá Pinto, AL, Lima, FR, Roschel, H, Gualano, B, Pinto, AJ, Meireles, K, Peçanha, T, Mazzolani, BC, Smaira, FI, Rezende, D, Benatti, FB, de Medeiros Ribeiro, AC, de Sá Pinto, AL, Lima, FR, Roschel, H, and Gualano, B
Abstract: Purpose: We investigated the effects of a 4-month intervention targeting sedentary behavior on sedentary time and physical activity level, clinical parameters, cardiometabolic risk factors, inflammatory markers, and health-related quality of life in post-menopausal women with rheumatoid arthritis. Methods: This was a 4-month, parallel-group, randomized controlled trial (ClinicalTrials.gov identifier: NCT03186924). One-hundred-and-three postmenopausal rheumatoid arthritis patients were randomized (1:1) to either a newly developed intervention targeting sedentary behavior (Take a STAND for Health; TS4H) or standard of care (SOC). Sedentary behavior (primary outcome) and physical activity levels, clinical parameters, anthropometric parameters and body composition, blood samples and oral glucose tolerance test, blood pressure, muscle function, and health-related quality of life were assessed at baseline (Pre) and after 4 months (Post). Between- and within-group differences were tested using linear mixed models following the intention-to-treat principle. Results: Total sedentary time, time in prolonged sitting bouts, standing, and stepping did not change in either group (all p≥0.337). No significant between- and within-group differences were detected for any of the clinical parameters, markers of cardiometabolic health and inflammation, and health-related quality of life variables (all p≥0.136). Among responders in TS4H group (those who reduced sedentary time by ≥30 min/d), Pre to Post IL-10 concentrations tended to reduce (group*time: p=0.086; estimated mean difference [EMD]: -12.0 pg/mL [-23.5 to -0.6], p=0.037), and general health (group*time: p=0.047; EMD: 10.9 A.U. [-1.1 to 22.9], p=0.086) and overall physical health tended to improve (group*time: p=0.067; EMD: 7.9 A.U. [-0.9 to 16.6], p=0.089). Conclusions: TS4H did not change sedentary behavior, physical activity levels, clinical, cardiometabolic, inflammatory or health-related quality of life outcomes. However, T
Published: 2025

2. New constraints on ultraheavy dark matter from the LZ experiment

Author: Aalbers, J, Aalbers, J, Akerib, DS, Al Musalhi, AK, Alder, F, Amarasinghe, CS, Ames, A, Anderson, TJ, Angelides, N, Araújo, HM, Armstrong, JE, Arthurs, M, Baker, A, Balashov, S, Bang, J, Barillier, EE, Bargemann, JW, Baxter, A, Beattie, K, Benson, T, Bhatti, A, Biekert, A, Biesiadzinski, TP, Birch, HJ, Bishop, EJ, Blockinger, GM, Boxer, B, Brew, CAJ, Brás, P, Burdin, S, Buuck, M, Carmona-Benitez, MC, Carter, M, Chawla, A, Chen, H, Cherwinka, JJ, Chin, YT, Chott, NI, Converse, MV, Cottle, A, Cox, G, Curran, D, Dahl, CE, David, A, Delgaudio, J, Dey, S, de Viveiros, L, Di Felice, L, Ding, C, Dobson, JEY, Druszkiewicz, E, Eriksen, SR, Fan, A, Fearon, NM, Fiorucci, S, Flaecher, H, Fraser, ED, Fruth, TMA, Gaitskell, RJ, Geffre, A, Genovesi, J, Ghag, C, Gibbons, R, Gokhale, S, Green, J, van der Grinten, MGD, Haiston, JH, Hall, CR, Han, S, Hartigan-O’Connor, E, Haselschwardt, SJ, Hernandez, MA, Hertel, SA, Heuermann, G, Homenides, GJ, Horn, M, Huang, DQ, Hunt, D, Ignarra, CM, Jacquet, E, James, RS, Johnson, J, Kaboth, AC, Kamaha, AC, Kannichankandy, M, Khaitan, D, Khazov, A, Khurana, I, Kim, J, Kingston, J, Kirk, R, Kodroff, D, Korley, L, Korolkova, EV, Kraus, H, Kravitz, S, Kreczko, L, Krikler, B, Kudryavtsev, VA, Lee, J, Leonard, DS, Aalbers, J, Aalbers, J, Akerib, DS, Al Musalhi, AK, Alder, F, Amarasinghe, CS, Ames, A, Anderson, TJ, Angelides, N, Araújo, HM, Armstrong, JE, Arthurs, M, Baker, A, Balashov, S, Bang, J, Barillier, EE, Bargemann, JW, Baxter, A, Beattie, K, Benson, T, Bhatti, A, Biekert, A, Biesiadzinski, TP, Birch, HJ, Bishop, EJ, Blockinger, GM, Boxer, B, Brew, CAJ, Brás, P, Burdin, S, Buuck, M, Carmona-Benitez, MC, Carter, M, Chawla, A, Chen, H, Cherwinka, JJ, Chin, YT, Chott, NI, Converse, MV, Cottle, A, Cox, G, Curran, D, Dahl, CE, David, A, Delgaudio, J, Dey, S, de Viveiros, L, Di Felice, L, Ding, C, Dobson, JEY, Druszkiewicz, E, Eriksen, SR, Fan, A, Fearon, NM, Fiorucci, S, Flaecher, H, Fraser, ED, Fruth, TMA, Gaitskell, RJ, Geffre, A, Genovesi, J, Ghag, C, Gibbons, R, Gokhale, S, Green, J, van der Grinten, MGD, Haiston, JH, Hall, CR, Han, S, Hartigan-O’Connor, E, Haselschwardt, SJ, Hernandez, MA, Hertel, SA, Heuermann, G, Homenides, GJ, Horn, M, Huang, DQ, Hunt, D, Ignarra, CM, Jacquet, E, James, RS, Johnson, J, Kaboth, AC, Kamaha, AC, Kannichankandy, M, Khaitan, D, Khazov, A, Khurana, I, Kim, J, Kingston, J, Kirk, R, Kodroff, D, Korley, L, Korolkova, EV, Kraus, H, Kravitz, S, Kreczko, L, Krikler, B, Kudryavtsev, VA, Lee, J, and Leonard, DS
Abstract: Searches for dark matter with liquid xenon time projection chamber experiments have traditionally focused on the region of the parameter space that is characteristic of weakly interacting massive particles, ranging from a few GeV/c2 to a few TeV/c2. Models of dark matter with a mass much heavier than this are well motivated by early production mechanisms different from the standard thermal freeze-out, but they have generally been less explored experimentally. In this work, we present a reanalysis of the first science run of the LZ experiment, with an exposure of 0.9 tonne×yr, to search for ultraheavy particle dark matter. The signal topology consists of multiple energy deposits in the active region of the detector forming a straight line, from which the velocity of the incoming particle can be reconstructed on an event-by-event basis. Zero events with this topology were observed after applying the data selection calibrated on a simulated sample of signal-like events. New experimental constraints are derived, which rule out previously unexplored regions of the dark matter parameter space of spin-independent interactions beyond a mass of 1017 GeV/c2.
Published: 2024

3. Biodiversity impacts of the 2019–2020 Australian megafires

Author: Driscoll, DA, Macdonald, KJ, Gibson, RK, Doherty, TS, Nimmo, DG, Nolan, RH, Ritchie, EG, Williamson, GJ, Heard, GW, Tasker, EM, Bilney, R, Porch, N, Collett, RA, Crates, RA, Hewitt, AC, Pendall, E, Boer, MM, Gates, J, Boulton, RL, Mclean, CM, Groffen, H, Maisey, AC, Beranek, CT, Ryan, SA, Callen, A, Hamer, AJ, Stauber, A, Daly, GJ, Gould, J, Klop-Toker, KL, Mahony, MJ, Kelly, OW, Wallace, SL, Stock, SE, Weston, CJ, Volkova, L, Black, D, Gibb, H, Grubb, JJ, McGeoch, MA, Murphy, NP, Lee, JS, Dickman, CR, Neldner, VJ, Ngugi, MR, Miritis, V, Köhler, F, Perri, M, Denham, AJ, Mackenzie, BDE, Reid, CAM, Rayment, JT, Arriaga-Jiménez, A, Hewins, MW, Hicks, A, Melbourne, BA, Davies, KF, Bitters, ME, Linley, GD, Greenville, AC, Webb, JK, Roberts, B, Letnic, M ; https://orcid.org/0000-0003-4191-8427, Price, OF, Walker, ZC, Murray, BR, Verhoeven, EM, Thomsen, AM, Keith, D ; https://orcid.org/0000-0002-7627-4150, Lemmon, JS, Ooi, MKJ ; https://orcid.org/0000-0002-3046-0417, Allen, VL, Decker, OT, Green, PT, Moussalli, A, Foon, JK, Bryant, DB, Walker, KL, Bruce, MJ, Madani, G, Tscharke, JL, Wagner, B, Nitschke, CR, Gosper, CR, Yates, CJ, Dillon, R, Barrett, S, Spencer, EE, Wardle, GM, Newsome, TM, Pulsford, SA, Singh, A, Roff, A, Marsh, KJ, Mcdonald, K, Howell, LG, Lane, MR, Cristescu, RH, Witt, RR, Cook, EJ, Le Breton, Tom, Driscoll, DA, Macdonald, KJ, Gibson, RK, Doherty, TS, Nimmo, DG, Nolan, RH, Ritchie, EG, Williamson, GJ, Heard, GW, Tasker, EM, Bilney, R, Porch, N, Collett, RA, Crates, RA, Hewitt, AC, Pendall, E, Boer, MM, Gates, J, Boulton, RL, Mclean, CM, Groffen, H, Maisey, AC, Beranek, CT, Ryan, SA, Callen, A, Hamer, AJ, Stauber, A, Daly, GJ, Gould, J, Klop-Toker, KL, Mahony, MJ, Kelly, OW, Wallace, SL, Stock, SE, Weston, CJ, Volkova, L, Black, D, Gibb, H, Grubb, JJ, McGeoch, MA, Murphy, NP, Lee, JS, Dickman, CR, Neldner, VJ, Ngugi, MR, Miritis, V, Köhler, F, Perri, M, Denham, AJ, Mackenzie, BDE, Reid, CAM, Rayment, JT, Arriaga-Jiménez, A, Hewins, MW, Hicks, A, Melbourne, BA, Davies, KF, Bitters, ME, Linley, GD, Greenville, AC, Webb, JK, Roberts, B, Letnic, M ; https://orcid.org/0000-0003-4191-8427, Price, OF, Walker, ZC, Murray, BR, Verhoeven, EM, Thomsen, AM, Keith, D ; https://orcid.org/0000-0002-7627-4150, Lemmon, JS, Ooi, MKJ ; https://orcid.org/0000-0002-3046-0417, Allen, VL, Decker, OT, Green, PT, Moussalli, A, Foon, JK, Bryant, DB, Walker, KL, Bruce, MJ, Madani, G, Tscharke, JL, Wagner, B, Nitschke, CR, Gosper, CR, Yates, CJ, Dillon, R, Barrett, S, Spencer, EE, Wardle, GM, Newsome, TM, Pulsford, SA, Singh, A, Roff, A, Marsh, KJ, Mcdonald, K, Howell, LG, Lane, MR, Cristescu, RH, Witt, RR, Cook, EJ, and Le Breton, Tom
Abstract: With large wildfires becoming more frequent1,2, we must rapidly learn how megafires impact biodiversity to prioritize mitigation and improve policy. A key challenge is to discover how interactions among fire-regime components, drought and land tenure shape wildfire impacts. The globally unprecedented3,4 2019–2020 Australian megafires burnt more than 10 million hectares5, prompting major investment in biodiversity monitoring. Collated data include responses of more than 2,000 taxa, providing an unparalleled opportunity to quantify how megafires affect biodiversity. We reveal that the largest effects on plants and animals were in areas with frequent or recent past fires and within extensively burnt areas. Areas burnt at high severity, outside protected areas or under extreme drought also had larger effects. The effects included declines and increases after fire, with the largest responses in rainforests and by mammals. Our results implicate species interactions, dispersal and extent of in situ survival as mechanisms underlying fire responses. Building wildfire resilience into these ecosystems depends on reducing fire recurrence, including with rapid wildfire suppression in areas frequently burnt. Defending wet ecosystems, expanding protected areas and considering localized drought could also contribute. While these countermeasures can help mitigate the impacts of more frequent megafires, reversing anthropogenic climate change remains the urgent broad-scale solution.
Published: 2024

4. Biodiversity impacts of the 2019-2020 Australian megafires.

Author: Driscoll, DA, Macdonald, KJ, Gibson, RK, Doherty, TS, Nimmo, DG, Nolan, RH, Ritchie, EG, Williamson, GJ, Heard, GW, Tasker, EM, Bilney, R, Porch, N, Collett, RA, Crates, RA, Hewitt, AC, Pendall, E, Boer, MM, Gates, J, Boulton, RL, Mclean, CM, Groffen, H, Maisey, AC, Beranek, CT, Ryan, SA, Callen, A, Hamer, AJ, Stauber, A, Daly, GJ, Gould, J, Klop-Toker, KL, Mahony, MJ, Kelly, OW, Wallace, SL, Stock, SE, Weston, CJ, Volkova, L, Black, D, Gibb, H, Grubb, JJ, McGeoch, MA, Murphy, NP, Lee, JS, Dickman, CR, Neldner, VJ, Ngugi, MR, Miritis, V, Köhler, F, Perri, M, Denham, AJ, Mackenzie, BDE, Reid, CAM, Rayment, JT, Arriaga-Jiménez, A, Hewins, MW, Hicks, A, Melbourne, BA, Davies, KF, Bitters, ME, Linley, GD, Greenville, AC, Webb, JK, Roberts, B, Letnic, M, Price, OF, Walker, ZC, Murray, BR, Verhoeven, EM, Thomsen, AM, Keith, D, Lemmon, JS, Ooi, MKJ, Allen, VL, Decker, OT, Green, PT, Moussalli, A, Foon, JK, Bryant, DB, Walker, KL, Bruce, MJ, Madani, G, Tscharke, JL, Wagner, B, Nitschke, CR, Gosper, CR, Yates, CJ, Dillon, R, Barrett, S, Spencer, EE, Wardle, GM, Newsome, TM, Pulsford, SA, Singh, A, Roff, A, Marsh, KJ, Mcdonald, K, Howell, LG, Lane, MR, Cristescu, RH, Witt, RR, Cook, EJ, Grant, F, Law, BS, Seddon, J, Berris, KK, Shofner, RM, Barth, M, Welz, T, Foster, A, Hancock, D, Beitzel, M, Tan, LXL, Waddell, NA, Fallow, PM, Schweickle, L, Le Breton, TD, Dunne, C, Green, M, Gilpin, A-M, Cook, JM, Power, SA, Hogendoorn, K, Brawata, R, Jolly, CJ, Tozer, M, Reiter, N, Phillips, RD, Driscoll, DA, Macdonald, KJ, Gibson, RK, Doherty, TS, Nimmo, DG, Nolan, RH, Ritchie, EG, Williamson, GJ, Heard, GW, Tasker, EM, Bilney, R, Porch, N, Collett, RA, Crates, RA, Hewitt, AC, Pendall, E, Boer, MM, Gates, J, Boulton, RL, Mclean, CM, Groffen, H, Maisey, AC, Beranek, CT, Ryan, SA, Callen, A, Hamer, AJ, Stauber, A, Daly, GJ, Gould, J, Klop-Toker, KL, Mahony, MJ, Kelly, OW, Wallace, SL, Stock, SE, Weston, CJ, Volkova, L, Black, D, Gibb, H, Grubb, JJ, McGeoch, MA, Murphy, NP, Lee, JS, Dickman, CR, Neldner, VJ, Ngugi, MR, Miritis, V, Köhler, F, Perri, M, Denham, AJ, Mackenzie, BDE, Reid, CAM, Rayment, JT, Arriaga-Jiménez, A, Hewins, MW, Hicks, A, Melbourne, BA, Davies, KF, Bitters, ME, Linley, GD, Greenville, AC, Webb, JK, Roberts, B, Letnic, M, Price, OF, Walker, ZC, Murray, BR, Verhoeven, EM, Thomsen, AM, Keith, D, Lemmon, JS, Ooi, MKJ, Allen, VL, Decker, OT, Green, PT, Moussalli, A, Foon, JK, Bryant, DB, Walker, KL, Bruce, MJ, Madani, G, Tscharke, JL, Wagner, B, Nitschke, CR, Gosper, CR, Yates, CJ, Dillon, R, Barrett, S, Spencer, EE, Wardle, GM, Newsome, TM, Pulsford, SA, Singh, A, Roff, A, Marsh, KJ, Mcdonald, K, Howell, LG, Lane, MR, Cristescu, RH, Witt, RR, Cook, EJ, Grant, F, Law, BS, Seddon, J, Berris, KK, Shofner, RM, Barth, M, Welz, T, Foster, A, Hancock, D, Beitzel, M, Tan, LXL, Waddell, NA, Fallow, PM, Schweickle, L, Le Breton, TD, Dunne, C, Green, M, Gilpin, A-M, Cook, JM, Power, SA, Hogendoorn, K, Brawata, R, Jolly, CJ, Tozer, M, Reiter, N, and Phillips, RD
Abstract: With large wildfires becoming more frequent1,2, we must rapidly learn how megafires impact biodiversity to prioritize mitigation and improve policy. A key challenge is to discover how interactions among fire-regime components, drought and land tenure shape wildfire impacts. The globally unprecedented3,4 2019-2020 Australian megafires burnt more than 10 million hectares5, prompting major investment in biodiversity monitoring. Collated data include responses of more than 2,000 taxa, providing an unparalleled opportunity to quantify how megafires affect biodiversity. We reveal that the largest effects on plants and animals were in areas with frequent or recent past fires and within extensively burnt areas. Areas burnt at high severity, outside protected areas or under extreme drought also had larger effects. The effects included declines and increases after fire, with the largest responses in rainforests and by mammals. Our results implicate species interactions, dispersal and extent of in situ survival as mechanisms underlying fire responses. Building wildfire resilience into these ecosystems depends on reducing fire recurrence, including with rapid wildfire suppression in areas frequently burnt. Defending wet ecosystems, expanding protected areas and considering localized drought could also contribute. While these countermeasures can help mitigate the impacts of more frequent megafires, reversing anthropogenic climate change remains the urgent broad-scale solution.
Published: 2024

5. Biodiversity impacts of the 2019-2020 Australian megafires.

Author: Driscoll, DA, Macdonald, KJ, Gibson, RK, Doherty, TS, Nimmo, DG, Nolan, RH, Ritchie, EG, Williamson, GJ, Heard, GW, Tasker, EM, Bilney, R, Porch, N, Collett, RA, Crates, RA, Hewitt, AC, Pendall, E, Boer, MM, Gates, J, Boulton, RL, Mclean, CM, Groffen, H, Maisey, AC, Beranek, CT, Ryan, SA, Callen, A, Hamer, AJ, Stauber, A, Daly, GJ, Gould, J, Klop-Toker, KL, Mahony, MJ, Kelly, OW, Wallace, SL, Stock, SE, Weston, CJ, Volkova, L, Black, D, Gibb, H, Grubb, JJ, McGeoch, MA, Murphy, NP, Lee, JS, Dickman, CR, Neldner, VJ, Ngugi, MR, Miritis, V, Köhler, F, Perri, M, Denham, AJ, Mackenzie, BDE, Reid, CAM, Rayment, JT, Arriaga-Jiménez, A, Hewins, MW, Hicks, A, Melbourne, BA, Davies, KF, Bitters, ME, Linley, GD, Greenville, AC, Webb, JK, Roberts, B, Letnic, M, Price, OF, Walker, ZC, Murray, BR, Verhoeven, EM, Thomsen, AM, Keith, D, Lemmon, JS, Ooi, MKJ, Allen, VL, Decker, OT, Green, PT, Moussalli, A, Foon, JK, Bryant, DB, Walker, KL, Bruce, MJ, Madani, G, Tscharke, JL, Wagner, B, Nitschke, CR, Gosper, CR, Yates, CJ, Dillon, R, Barrett, S, Spencer, EE, Wardle, GM, Newsome, TM, Pulsford, SA, Singh, A, Roff, A, Marsh, KJ, Mcdonald, K, Howell, LG, Lane, MR, Cristescu, RH, Witt, RR, Cook, EJ, Grant, F, Law, BS, Seddon, J, Berris, KK, Shofner, RM, Barth, M, Welz, T, Foster, A, Hancock, D, Beitzel, M, Tan, LXL, Waddell, NA, Fallow, PM, Schweickle, L, Le Breton, TD, Dunne, C, Green, M, Gilpin, A-M, Cook, JM, Power, SA, Hogendoorn, K, Brawata, R, Jolly, CJ, Tozer, M, Reiter, N, Phillips, RD, Driscoll, DA, Macdonald, KJ, Gibson, RK, Doherty, TS, Nimmo, DG, Nolan, RH, Ritchie, EG, Williamson, GJ, Heard, GW, Tasker, EM, Bilney, R, Porch, N, Collett, RA, Crates, RA, Hewitt, AC, Pendall, E, Boer, MM, Gates, J, Boulton, RL, Mclean, CM, Groffen, H, Maisey, AC, Beranek, CT, Ryan, SA, Callen, A, Hamer, AJ, Stauber, A, Daly, GJ, Gould, J, Klop-Toker, KL, Mahony, MJ, Kelly, OW, Wallace, SL, Stock, SE, Weston, CJ, Volkova, L, Black, D, Gibb, H, Grubb, JJ, McGeoch, MA, Murphy, NP, Lee, JS, Dickman, CR, Neldner, VJ, Ngugi, MR, Miritis, V, Köhler, F, Perri, M, Denham, AJ, Mackenzie, BDE, Reid, CAM, Rayment, JT, Arriaga-Jiménez, A, Hewins, MW, Hicks, A, Melbourne, BA, Davies, KF, Bitters, ME, Linley, GD, Greenville, AC, Webb, JK, Roberts, B, Letnic, M, Price, OF, Walker, ZC, Murray, BR, Verhoeven, EM, Thomsen, AM, Keith, D, Lemmon, JS, Ooi, MKJ, Allen, VL, Decker, OT, Green, PT, Moussalli, A, Foon, JK, Bryant, DB, Walker, KL, Bruce, MJ, Madani, G, Tscharke, JL, Wagner, B, Nitschke, CR, Gosper, CR, Yates, CJ, Dillon, R, Barrett, S, Spencer, EE, Wardle, GM, Newsome, TM, Pulsford, SA, Singh, A, Roff, A, Marsh, KJ, Mcdonald, K, Howell, LG, Lane, MR, Cristescu, RH, Witt, RR, Cook, EJ, Grant, F, Law, BS, Seddon, J, Berris, KK, Shofner, RM, Barth, M, Welz, T, Foster, A, Hancock, D, Beitzel, M, Tan, LXL, Waddell, NA, Fallow, PM, Schweickle, L, Le Breton, TD, Dunne, C, Green, M, Gilpin, A-M, Cook, JM, Power, SA, Hogendoorn, K, Brawata, R, Jolly, CJ, Tozer, M, Reiter, N, and Phillips, RD
Abstract: With large wildfires becoming more frequent1,2, we must rapidly learn how megafires impact biodiversity to prioritize mitigation and improve policy. A key challenge is to discover how interactions among fire-regime components, drought and land tenure shape wildfire impacts. The globally unprecedented3,4 2019-2020 Australian megafires burnt more than 10 million hectares5, prompting major investment in biodiversity monitoring. Collated data include responses of more than 2,000 taxa, providing an unparalleled opportunity to quantify how megafires affect biodiversity. We reveal that the largest effects on plants and animals were in areas with frequent or recent past fires and within extensively burnt areas. Areas burnt at high severity, outside protected areas or under extreme drought also had larger effects. The effects included declines and increases after fire, with the largest responses in rainforests and by mammals. Our results implicate species interactions, dispersal and extent of in situ survival as mechanisms underlying fire responses. Building wildfire resilience into these ecosystems depends on reducing fire recurrence, including with rapid wildfire suppression in areas frequently burnt. Defending wet ecosystems, expanding protected areas and considering localized drought could also contribute. While these countermeasures can help mitigate the impacts of more frequent megafires, reversing anthropogenic climate change remains the urgent broad-scale solution.
Published: 2024

6. RATIONING PUBLIC LANDS

Author: Lin, AC, Lin, AC, Lin, AC, and Lin, AC
Abstract: Visitation at national parks and other public lands has surged to record levels, a trend intensified in many places by the COVID-19 pandemic. Unfortunately, the popularity of public lands has led to congestion, a degraded outdoor experience, and damage to natural resources. In response, land managers have adopted capacity limits, reservation requirements, and other access restrictions. The growing restrictions on access to public lands raise serious concerns. They threaten individual benefits that public lands generate for physical and mental health, as well as collective benefits to cultural identity and national unity. Restrictions on access often have disparate impacts on those who are economically disadvantaged or lack technological savvy. In addition, land managers sometimes institute these restrictions with little or no notice or opportunity for public input. Although public land managers have various tools to accommodate high visitation, they sometimes have to ration access to public lands. Closures and other restrictions may be necessary to ensure public safety, maintain the quality of visitor experiences, or protect wildlife and other resources. This Article explores guidelines to assist land managers as they make difficult decisions about the restriction and allocation of access to public lands.
Published: 2024

7. First constraints on WIMP-nucleon effective field theory couplings in an extended energy region from LUX-ZEPLIN

Author: Aalbers, J, Aalbers, J, Akerib, DS, Al Musalhi, AK, Alder, F, Amarasinghe, CS, Ames, A, Anderson, TJ, Angelides, N, Araújo, HM, Armstrong, JE, Arthurs, M, Baker, A, Balashov, S, Bang, J, Bargemann, JW, Baxter, A, Beattie, K, Benson, T, Bhatti, A, Biekert, A, Biesiadzinski, TP, Birch, HJ, Bishop, E, Blockinger, GM, Boxer, B, Brew, CAJ, Brás, P, Burdin, S, Buuck, M, Carmona-Benitez, MC, Carter, M, Chawla, A, Chen, H, Cherwinka, JJ, Chott, NI, Converse, MV, Cottle, A, Cox, G, Curran, D, Dahl, CE, David, A, Delgaudio, J, Dey, S, de Viveiros, L, Ding, C, Dobson, JEY, Druszkiewicz, E, Eriksen, SR, Fan, A, Fearon, NM, Fiorucci, S, Flaecher, H, Fraser, ED, Fruth, TMA, Gaitskell, RJ, Geffre, A, Genovesi, J, Ghag, C, Gibbons, R, Gokhale, S, Green, J, van der Grinten, MGD, Hall, CR, Han, S, Hartigan-O’Connor, E, Haselschwardt, SJ, Hernandez, MA, Hertel, SA, Heuermann, G, Homenides, GJ, Horn, M, Huang, DQ, Hunt, D, Ignarra, CM, Jacquet, E, James, RS, Johnson, J, Kaboth, AC, Kamaha, AC, Khaitan, D, Khazov, A, Khurana, I, Kim, J, Kingston, J, Kirk, R, Kodroff, D, Korley, L, Korolkova, EV, Kraus, H, Kravitz, S, Kreczko, L, Krikler, B, Kudryavtsev, VA, Lee, J, Leonard, DS, Lesko, KT, Levy, C, Lin, J, Lindote, A, Linehan, R, Aalbers, J, Aalbers, J, Akerib, DS, Al Musalhi, AK, Alder, F, Amarasinghe, CS, Ames, A, Anderson, TJ, Angelides, N, Araújo, HM, Armstrong, JE, Arthurs, M, Baker, A, Balashov, S, Bang, J, Bargemann, JW, Baxter, A, Beattie, K, Benson, T, Bhatti, A, Biekert, A, Biesiadzinski, TP, Birch, HJ, Bishop, E, Blockinger, GM, Boxer, B, Brew, CAJ, Brás, P, Burdin, S, Buuck, M, Carmona-Benitez, MC, Carter, M, Chawla, A, Chen, H, Cherwinka, JJ, Chott, NI, Converse, MV, Cottle, A, Cox, G, Curran, D, Dahl, CE, David, A, Delgaudio, J, Dey, S, de Viveiros, L, Ding, C, Dobson, JEY, Druszkiewicz, E, Eriksen, SR, Fan, A, Fearon, NM, Fiorucci, S, Flaecher, H, Fraser, ED, Fruth, TMA, Gaitskell, RJ, Geffre, A, Genovesi, J, Ghag, C, Gibbons, R, Gokhale, S, Green, J, van der Grinten, MGD, Hall, CR, Han, S, Hartigan-O’Connor, E, Haselschwardt, SJ, Hernandez, MA, Hertel, SA, Heuermann, G, Homenides, GJ, Horn, M, Huang, DQ, Hunt, D, Ignarra, CM, Jacquet, E, James, RS, Johnson, J, Kaboth, AC, Kamaha, AC, Khaitan, D, Khazov, A, Khurana, I, Kim, J, Kingston, J, Kirk, R, Kodroff, D, Korley, L, Korolkova, EV, Kraus, H, Kravitz, S, Kreczko, L, Krikler, B, Kudryavtsev, VA, Lee, J, Leonard, DS, Lesko, KT, Levy, C, Lin, J, Lindote, A, and Linehan, R
Abstract: Following the first science results of the LUX-ZEPLIN (LZ) experiment, a dual-phase xenon time projection chamber operating from the Sanford Underground Research Facility in Lead, South Dakota, USA, we report the initial limits on a model-independent nonrelativistic effective field theory describing the complete set of possible interactions of a weakly interacting massive particle (WIMP) with a nucleon. These results utilize the same 5.5 t fiducial mass and 60 live days of exposure collected for the LZ spin-independent and spin-dependent analyses while extending the upper limit of the energy region of interest by a factor of 7.5 to 270 keV. No significant excess in this high energy region is observed. Using a profile-likelihood ratio analysis, we report 90% confidence level exclusion limits on the coupling of each individual nonrelativistic WIMP-nucleon operator for both elastic and inelastic interactions in the isoscalar and isovector bases.
Published: 2024

8. The design, implementation, and performance of the LZ calibration systems

Author: Aalbers, J, Aalbers, J, Akerib, DS, Al Musalhi, AK, Alder, F, Amarasinghe, CS, Ames, A, Anderson, TJ, Angelides, N, Araújo, HM, Armstrong, JE, Arthurs, M, Baker, A, Balashov, S, Bang, J, Barillier, EE, Bargemann, JW, Beattie, K, Benson, T, Bhatti, A, Biekert, A, Biesiadzinski, TP, Birch, HJ, Bishop, E, Blockinger, GM, Boxer, B, Brew, CAJ, Brás, P, Burdin, S, Buuck, M, Carmona-Benitez, MC, Carter, M, Chawla, A, Chen, H, Cherwinka, JJ, Chin, YT, Chott, NI, Converse, MV, Cottle, A, Cox, G, Curran, D, Dahl, CE, David, A, Delgaudio, J, Dey, S, de Viveiros, L, Di Felice, L, Ding, C, Dobson, JEY, Druszkiewicz, E, Eriksen, SR, Fan, A, Fearon, NM, Fieldhouse, N, Fiorucci, S, Flaecher, H, Fraser, ED, Fruth, TMA, Gaitskell, RJ, Geffre, A, Genovesi, J, Ghag, C, Gibbons, R, Gokhale, S, Green, J, van der Grinten, MGD, Haiston, JJ, Hall, CR, Han, S, Hartigan-O'Connor, E, Haselschwardt, SJ, Hernandez, MA, Hertel, SA, Heuermann, G, Homenides, GJ, Horn, M, Huang, DQ, Hunt, D, Jacquet, E, James, RS, Johnson, J, Kaboth, AC, Kamaha, AC, Kannichankandy, M, Khaitan, D, Khazov, A, Khurana, I, Kim, J, Kim, YD, Kingston, J, Kirk, R, Kodroff, D, Korley, L, Korolkova, EV, Kraus, H, Kravitz, S, Kreczko, L, Kudryavtsev, VA, Leonard, DS, Lesko, KT, Levy, C, Aalbers, J, Aalbers, J, Akerib, DS, Al Musalhi, AK, Alder, F, Amarasinghe, CS, Ames, A, Anderson, TJ, Angelides, N, Araújo, HM, Armstrong, JE, Arthurs, M, Baker, A, Balashov, S, Bang, J, Barillier, EE, Bargemann, JW, Beattie, K, Benson, T, Bhatti, A, Biekert, A, Biesiadzinski, TP, Birch, HJ, Bishop, E, Blockinger, GM, Boxer, B, Brew, CAJ, Brás, P, Burdin, S, Buuck, M, Carmona-Benitez, MC, Carter, M, Chawla, A, Chen, H, Cherwinka, JJ, Chin, YT, Chott, NI, Converse, MV, Cottle, A, Cox, G, Curran, D, Dahl, CE, David, A, Delgaudio, J, Dey, S, de Viveiros, L, Di Felice, L, Ding, C, Dobson, JEY, Druszkiewicz, E, Eriksen, SR, Fan, A, Fearon, NM, Fieldhouse, N, Fiorucci, S, Flaecher, H, Fraser, ED, Fruth, TMA, Gaitskell, RJ, Geffre, A, Genovesi, J, Ghag, C, Gibbons, R, Gokhale, S, Green, J, van der Grinten, MGD, Haiston, JJ, Hall, CR, Han, S, Hartigan-O'Connor, E, Haselschwardt, SJ, Hernandez, MA, Hertel, SA, Heuermann, G, Homenides, GJ, Horn, M, Huang, DQ, Hunt, D, Jacquet, E, James, RS, Johnson, J, Kaboth, AC, Kamaha, AC, Kannichankandy, M, Khaitan, D, Khazov, A, Khurana, I, Kim, J, Kim, YD, Kingston, J, Kirk, R, Kodroff, D, Korley, L, Korolkova, EV, Kraus, H, Kravitz, S, Kreczko, L, Kudryavtsev, VA, Leonard, DS, Lesko, KT, and Levy, C
Abstract: LUX-ZEPLIN (LZ) is a tonne-scale experiment searching for direct dark matter interactions and other rare events. It is located at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, USA. The core of the LZ detector is a dual-phase xenon time projection chamber (TPC), designed with the primary goal of detecting Weakly Interacting Massive Particles (WIMPs) via their induced low energy nuclear recoils. Surrounding the TPC, two veto detectors immersed in an ultra-pure water tank enable reducing background events to enhance the discovery potential. Intricate calibration systems are purposely designed to precisely understand the responses of these three detector volumes to various types of particle interactions and to demonstrate LZ’s ability to discriminate between signals and backgrounds. In this paper, we present a comprehensive discussion of the key features, requirements, and performance of the LZ calibration systems, which play a crucial role in enabling LZ’s WIMP-search and its broad science program. The thorough description of these calibration systems, with an emphasis on their novel aspects, is valuable for future calibration efforts in direct dark matter and other rare-event search experiments.
Published: 2024

9. The data acquisition system of the LZ dark matter detector: FADR

Author: Aalbers, J, Aalbers, J, Akerib, DS, Al Musalhi, AK, Alder, F, Amarasinghe, CS, Ames, A, Anderson, TJ, Angelides, N, Araújo, HM, Armstrong, JE, Arthurs, M, Baker, A, Balashov, S, Bang, J, Barillier, EE, Bargemann, JW, Beattie, K, Benson, T, Bhatti, A, Biekert, A, Biesiadzinski, TP, Birch, HJ, Bishop, E, Blockinger, GM, Boxer, B, Brew, CAJ, Brás, P, Buckley, JH, Burdin, S, Buuck, M, Carmona-Benitez, MC, Carter, M, Chawla, A, Chen, H, Cherwinka, JJ, Chin, YT, Chott, NI, Converse, MV, Cottle, A, Cox, G, Curran, D, Dahl, CE, David, A, Delgaudio, J, Dey, S, de Viveiros, L, Di Felice, L, Dimino, T, Ding, C, Dobson, JEY, Druszkiewicz, E, Eriksen, SR, Fan, A, Fearon, NM, Fieldhouse, N, Fiorucci, S, Flaecher, H, Fraser, ED, Fruth, TMA, Gaitskell, RJ, Geffre, A, Gelfand, R, Genovesi, J, Ghag, C, Gibbons, R, Gokhale, S, Green, J, van der Grinten, MGD, Haiston, JJ, Hall, CR, Han, S, Hartigan-O’Connor, E, Haselschwardt, SJ, Hernandez, MA, Hertel, SA, Heuermann, G, Homenides, GJ, Horn, M, Huang, DQ, Hunt, D, Jacquet, E, James, RS, Johnson, J, Kaboth, AC, Kamaha, AC, Kannichankandy, M, Khaitan, D, Khazov, A, Khurana, I, Kim, J, Kim, YD, Kingston, J, Kirk, R, Kodroff, D, Korley, L, Korolkova, EV, Koyuncu, M, Kraus, H, Kravitz, S, Kreczko, L, Aalbers, J, Aalbers, J, Akerib, DS, Al Musalhi, AK, Alder, F, Amarasinghe, CS, Ames, A, Anderson, TJ, Angelides, N, Araújo, HM, Armstrong, JE, Arthurs, M, Baker, A, Balashov, S, Bang, J, Barillier, EE, Bargemann, JW, Beattie, K, Benson, T, Bhatti, A, Biekert, A, Biesiadzinski, TP, Birch, HJ, Bishop, E, Blockinger, GM, Boxer, B, Brew, CAJ, Brás, P, Buckley, JH, Burdin, S, Buuck, M, Carmona-Benitez, MC, Carter, M, Chawla, A, Chen, H, Cherwinka, JJ, Chin, YT, Chott, NI, Converse, MV, Cottle, A, Cox, G, Curran, D, Dahl, CE, David, A, Delgaudio, J, Dey, S, de Viveiros, L, Di Felice, L, Dimino, T, Ding, C, Dobson, JEY, Druszkiewicz, E, Eriksen, SR, Fan, A, Fearon, NM, Fieldhouse, N, Fiorucci, S, Flaecher, H, Fraser, ED, Fruth, TMA, Gaitskell, RJ, Geffre, A, Gelfand, R, Genovesi, J, Ghag, C, Gibbons, R, Gokhale, S, Green, J, van der Grinten, MGD, Haiston, JJ, Hall, CR, Han, S, Hartigan-O’Connor, E, Haselschwardt, SJ, Hernandez, MA, Hertel, SA, Heuermann, G, Homenides, GJ, Horn, M, Huang, DQ, Hunt, D, Jacquet, E, James, RS, Johnson, J, Kaboth, AC, Kamaha, AC, Kannichankandy, M, Khaitan, D, Khazov, A, Khurana, I, Kim, J, Kim, YD, Kingston, J, Kirk, R, Kodroff, D, Korley, L, Korolkova, EV, Koyuncu, M, Kraus, H, Kravitz, S, and Kreczko, L
Abstract: The Data Acquisition System (DAQ) for the LUX-ZEPLIN (LZ) dark matter detector is described. The signals from 745 PMTs, distributed across three subsystems, are sampled with 100-MHz 32-channel digitizers (DDC-32s). A basic waveform analysis is carried out on the on-board Field Programmable Gate Arrays (FPGAs) to extract information about the observed scintillation and electroluminescence signals. This information is used to determine if the digitized waveforms should be preserved for offline analysis. The system is designed around the Kintex-7 FPGA. In addition to digitizing the PMT signals and providing basic event selection in real time, the flexibility provided by the use of FPGAs allows us to monitor the performance of the detector and the DAQ in parallel to normal data acquisition. The hardware and software/firmware of this FPGA-based Architecture for Data acquisition and Realtime monitoring (FADR) are discussed and performance measurements are described.
Published: 2024

10. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Brauer, M, Roth, GA, Aravkin, AY, Zheng, P, Abate, KH, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasi, MA, Abbasian, M, Abbasifard, M, Moradi, Y, Bensenor, IM, Benzian, H, Beran, A, Abouzid, M, Berezvai, Z, Bernabe, E, Bernstein, RS, Bettencourt, PJG, Bhagavathula, AS, Bhala, N, Moraga, P, Bhandari, D, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Aboye, GB, Bhat, AN, Bhat, V, Bhatti, GK, Bhatti, JS, Bhatti, MS, Morawska, L, Bhatti, R, Bhuiyan, MA, Bhutta, ZA, Bikbov, B, Bishai, JD, Abreu, LG, Bisignano, C, Biswas, A, Biswas, B, Biswas, RK, Moreira, RS, Bjørge, T, Boachie, MK, Boakye, H, Bockarie, MJ, Bodolica, V, Bodunrin, AO, Abualruz, H, Bogale, EK, Bolla, SR, Boloor, A, Morovatdar, N, Bonakdar Hashemi, M, Boppana, SH, Bora Basara, B, Borhany, H, Botero Carvajal, A, Bouaoud, S, Boufous, S, Abubakar, B, Bourne, R, Boxe, C, Morrison, SD, Braithwaite, D, Brant, LC, Brar, A, Breitborde, NJK, Breitner, S, Brenner, H, Briko, AN, Britton, G, Abu-Gharbieh, E, Brown, CS, Morze, J, Browne, AJ, Brunoni, AR, Bryazka, D, Bulamu, NB, Bulto, LN, Buonsenso, D, Burkart, K, Burns, RA, Busse, R, Abukhadijah, HJJ, Mosaddeghi Heris, R, Bustanji, Y, Butt, NS, Butt, ZA, Caetano dos Santos, FL, Cagney, J, Cahuana-Hurtado, L, Calina, D, Cámera, LA, Campos, LA, Campos-Nonato, IR, Mossialos, E, Aburuz, S, Cao, C, Cao, F, Cao, Y, Capodici, A, Cárdenas, R, Carr, S, Carreras, G, Carrero, JJ, Carugno, A, Motappa, R, Carvalho, F, Abu-Zaid, A, Carvalho, M, Castaldelli-Maia, JM, Castañeda-Orjuela, CA, Castelpietra, G, Catalá-López, F, Catapano, AL, Cattaruzza, MS, Caye, A, Alemayohu, MA, Ali, BA, Cederroth, CR, Cegolon, L, Adane, MM, Cenderadewi, M, Cercy, KM, Cerin, E, Chadwick, J, Chakraborty, C, Chakraborty, PA, Chakraborty, S, Mougin, V, Chan, JSK, Chan, RNC, Chandan, JS, Addo, IY, Chandika, RM, Chaturvedi, P, Chen, A-T, Chen, CS, Chen, H, Chen, MX, Mousavi, P, Chen, M, Chen, S, Cheng, C-Y, Cheng, ETW, Addolorato, G, Cherbuin, N, Chi, G, Chichagi, F, Chimed-Ochir, O, Chimoriya, R, Msherghi, A, Ching, PR, Chirinos-Caceres, JL, Chitheer, A, Cho, WCS, Chong, B, Adedoyin, RA, Chopra, H, Chowdhury, R, Christopher, DJ, Chu, D-T, Mubarik, S, Chukwu, IS, Chung, E, Chung, S-C, Chutiyami, M, Cioffi, I, Cogen, RM, Adekanmbi, V, Cohen, AJ, Columbus, A, Conde, J, Muccioli, L, Corlateanu, A, Cortese, S, Cortesi, PA, Costa, VM, Costanzo, S, Criqui, MH, Cruz, JA, Aden, B, Cruz-Martins, N, Culbreth, GT, Mueller, UO, da Silva, AG, Dadras, O, Dai, X, Dai, Z, Daikwo, PU, Dalli, LL, Damiani, G, D'Amico, E, Adetunji, JB, D'Anna, L, Mulita, F, Darwesh, AM, Das, JK, Das, S, Dash, NR, Dashti, M, Dávila-Cervantes, CA, Davis Weaver, N, Davitoiu, DV, De la Hoz, FP, Adeyeoluwa, TE, Mullany, EC, de la Torre-Luque, A, De Leo, D, Debopadhaya, S, Degenhardt, L, Del Bo', C, Delgado-Enciso, I, Delgado-Saborit, JM, Demoze, CK, Denova-Gutiérrez, E, Dervenis, N, Munjal, K, Adha, R, Dervišević, E, Desai, HD, Desai, R, Devanbu, VGC, Dewan, SMR, Dhali, A, Dhama, K, Dhane, AS, Dhimal, ML, Marx, W, Murillo-Zamora, E, Dhimal, M, Adibi, A, Dhingra, S, Dhulipala, VR, Dhungana, RR, Dias da Silva, D, Diaz, D, Diaz, LA, Diaz, MJ, Dima, A, Abbasi-Kangevari, M, Ding, DD, Dinu, M, Adnani, QES, Djalalinia, S, Do, TC, Do, THP, do Prado, CB, Dodangeh, M, Dohare, S, Dokova, KG, Ali, I, Dong, W, Dongarwar, D, D'Oria, M, Adzigbli, LA, Dorostkar, F, Dorsey, ER, Doshi, R, Doshmangir, L, Dowou, RK, Driscoll, TR, Murlimanju, BV, Dsouza, AC, Dsouza, HL, Dumith, SC, Duncan, BB, Afolabi, AA, Duraes, AR, Duraisamy, S, Dushpanova, A, Dzianach, PA, Dziedzic, AM, Musina, A-M, Ebrahimi, A, Echieh, CP, Ed-Dra, A, Edinur, HA, Edvardsson, D, Afolabi, RF, Edvardsson, K, Efendi, F, Eftekharimehrabad, A, Eini, E, Mustafa, G, Ekholuenetale, M, Ekundayo, TC, El Arab, RA, El Sayed Zaki, M, El-Dahiyat, F, Elemam, NM, Afshin, A, Elgar, FJ, ElGohary, GMT, Elhabashy, HR, Muthu, S, Elhadi, M, Elmehrath, AO, Elmeligy, OAA, Elshaer, M, Elsohaby, I, Emeto, TI, Esfandiari, N, Afyouni, S, Eshrati, B, Eslami, M, Muthupandian, S, Esmaeili, SV, Estep, K, Etaee, F, Fabin, N, Fagbamigbe, AF, Fagbule, OF, Fahimi, S, Falzone, L, Afzal, MS, Fareed, M, Muthusamy, R, Farinha, CSES, Faris, MEM, Faris, PS, Faro, A, Fasina, FO, Fatehizadeh, A, Fauk, NK, Fazylov, T, Feigin, VL, Afzal, S, Muzaffar, M, Feng, X, Fereshtehnejad, S-M, Feroze, AH, Ferrara, P, Ferrari, AJ, Ferreira, N, Fetensa, G, Feyisa, BR, Filip, I, Fischer, F, Maryam, S, Myung, W, Agampodi, SB, Fitriana, I, Flavel, J, Flohr, C, Flood, D, Flor, LS, Foigt, NA, Folayan, MO, Force, LM, Fortuna, D, Nafei, A, Foschi, M, Agbozo, F, Franklin, RC, Freitas, A, Friedman, SD, Fux, B, G, S, Gaal, PA, Gaihre, S, Gajdács, M, Nagarajan, AJ, Galali, Y, Gallus, S, Aghamiri, S, Gandhi, AP, Ganesan, B, Ganiyani, MA, Garcia, V, Gardner, WM, Garg, RK, Gautam, RK, Ali, L, Gebi, TG, Gebregergis, MW, Gebrehiwot, M, Agodi, A, Gebremariam, TBB, Gebremeskel, TG, Gerema, U, Getacher, L, Getahun, GKA, Getie, M, Nagaraju, SP, Ghadirian, F, Ghafarian, S, Ghaffari Jolfayi, A, Ghailan, KY, Agrawal, A, Ghajar, A, Ghasemi, M, Ghasempour Dabaghi, G, Ghasemzadeh, A, Ghassemi, F, Nagel, G, Ghazy, RM, Gholami, A, Gholamrezanezhad, A, Gholizadeh, N, Ghorbani, M, Agyemang-Duah, W, Gil, AU, Gil, GF, Gilbertson, NM, Gill, PS, Naghavi, M, Gill, TK, Gindaba, EZ, Girmay, A, Glasbey, JC, Gnedovskaya, EV, Göbölös, L, Ahinkorah, BO, Godinho, MA, Goel, A, Golechha, M, Naghavi, P, Goleij, P, Golinelli, D, Gomes, NGM, Gopalani, SV, Gorini, G, Goudarzi, H, Goulart, AC, Ahmad, A, Gouravani, M, Goyal, A, Naik, GR, Graham, SM, Grivna, M, Grosso, G, Guan, S-Y, Guarducci, G, Gubari, MIM, Guha, A, Guicciardi, S, Ahmad, D, Gulati, S, Naik, G, Gulisashvili, D, Gunawardane, DA, Guo, C, Gupta, AK, Gupta, B, Gupta, M, Gupta, R, Gupta, RD, Ahmad, F, Mathangasinghe, Y, Nainu, F, Gupta, S, Gupta, VB, Gupta, VK, Habibzadeh, F, Habibzadeh, P, Hadaro, TS, Hadian, Z, Haep, N, Haghi-Aminjan, H, Nair, TS, Ahmad, N, Haghmorad, D, Hagins, H, Haile, D, Hailu, A, Hajj Ali, A, Halboub, ES, 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Zastrozhin, MS, Zeng, Y, Zhai, C, Mohammadifard, N, Zhang, AL, Zhang, H, Zhang, L, Zhang, M, Zhang, Y, Anwer, R, Zhang, Z, Zhang, Z-J, Zhao, H, Zhao, JT, Mohammed, H, Zhao, X-JG, Zhao, Y, Zhong, C, Zhou, J, Anyabolo, EE, Zhou, S, Zhu, B, Zhu, L, Ali, A, Zhu, Z, Ziaeian, B, Ziafati, M, Zielińska, M, Zimsen, SRM, Zoghi, G, Zoller, T, Anyasodor, AE, Zumla, A, Zyoud, SH, Mohammed, M, Murray, CJL, Gakidou, E, Abdullahi, A, Apostol, GLC, Arabloo, J, Arabzadeh Bahri, R, Arafat, M, Areda, D, Aregawi, BB, Mohammed, S, Aremu, A, Armocida, B, Arndt, MB, Ärnlöv, J, Abebe, M, Arooj, M, Artamonov, AA, Artanti, KD, Aruleba, IT, Arumugam, A, Asbeutah, AM, Asgary, S, Asgedom, AA, Ashbaugh, C, Ashemo, MY, Abedi, A, Ashraf, T, Askarinejad, A, Assmus, M, Astell-Burt, T, Mokdad, AH, Athar, M, Athari, SS, Atorkey, P, Atreya, A, Aujayeb, A, Ausloos, M, Avila-Burgos, L, Awoke, AA, Ayala Quintanilla, BP, Monasta, L, Ayatollahi, H, Ayestas Portugal, C, Ayuso-Mateos, JL, Azadnajafabad, S, Azevedo, RMS, Azhar, GS, Azizi, H, Abegaz, TM, Azzam, AY, Backhaus, IL, Mondello, S, Badar, M, Badiye, AD, Bagga, A, Baghdadi, S, Bagheri, N, Bagherieh, S, Bahrami Taghanaki, P, Bai, R, Abeldaño Zuñiga, RA, Baig, AA, Moni, MA, Baker, JL, Bakkannavar, SM, Balasubramanian, M, Baltatu, OC, Bam, K, Bandyopadhyay, S, Banik, B, Banik, PC, Banke-Thomas, A, Abiodun, O, Moodi Ghalibaf, A, Bansal, H, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, SL, Bärnighausen, TW, Barone-Adesi, F, Barqawi, HJ, Barrero, LH, Barrow, A, Moore, CE, Abiso, TL, Barteit, S, Basharat, Z, Basiru, A, Basso, JD, Bastan, M-M, Basu, S, Batchu, S, Batra, K, Batra, R, Moradi, M, Baune, BT, Aboagye, RG, Bayati, M, Bayileyegn, NS, Beaney, T, Behnoush, AH, Beiranvand, M, Béjot, Y, Bekele, A, Belgaumi, UI, Bell, AW, Bell, ML, Abolhassani, H, Bello, MB, Bello, OO, Belo, L, Beloukas, A, Bendak, S, Bennett, DA, and Bennitt, FB
Published: 2024

11. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Brauer, M, Roth, GA, Aravkin, AY, Zheng, P, Abate, KH, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasi, MA, Abbasian, M, Abbasifard, M, Moradi, Y, Bensenor, IM, Benzian, H, Beran, A, Abouzid, M, Berezvai, Z, Bernabe, E, Bernstein, RS, Bettencourt, PJG, Bhagavathula, AS, Bhala, N, Moraga, P, Bhandari, D, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Aboye, GB, Bhat, AN, Bhat, V, Bhatti, GK, Bhatti, JS, Bhatti, MS, Morawska, L, Bhatti, R, Bhuiyan, MA, Bhutta, ZA, Bikbov, B, Bishai, JD, Abreu, LG, Bisignano, C, Biswas, A, Biswas, B, Biswas, RK, Moreira, RS, Bjørge, T, Boachie, MK, Boakye, H, Bockarie, MJ, Bodolica, V, Bodunrin, AO, Abualruz, H, Bogale, EK, Bolla, SR, Boloor, A, Morovatdar, N, Bonakdar Hashemi, M, Boppana, SH, Bora Basara, B, Borhany, H, Botero Carvajal, A, Bouaoud, S, Boufous, S, Abubakar, B, Bourne, R, Boxe, C, Morrison, SD, Braithwaite, D, Brant, LC, Brar, A, Breitborde, NJK, Breitner, S, Brenner, H, Briko, AN, Britton, G, Abu-Gharbieh, E, Brown, CS, Morze, J, Browne, AJ, Brunoni, AR, Bryazka, D, Bulamu, NB, Bulto, LN, Buonsenso, D, Burkart, K, Burns, RA, Busse, R, Abukhadijah, HJJ, Mosaddeghi Heris, R, Bustanji, Y, Butt, NS, Butt, ZA, Caetano dos Santos, FL, Cagney, J, Cahuana-Hurtado, L, Calina, D, Cámera, LA, Campos, LA, Campos-Nonato, IR, Mossialos, E, Aburuz, S, Cao, C, Cao, F, Cao, Y, Capodici, A, Cárdenas, R, Carr, S, Carreras, G, Carrero, JJ, Carugno, A, Motappa, R, Carvalho, F, Abu-Zaid, A, Carvalho, M, Castaldelli-Maia, JM, Castañeda-Orjuela, CA, Castelpietra, G, Catalá-López, F, Catapano, AL, Cattaruzza, MS, Caye, A, Alemayohu, MA, Ali, BA, Cederroth, CR, Cegolon, L, Adane, MM, Cenderadewi, M, Cercy, KM, Cerin, E, Chadwick, J, Chakraborty, C, Chakraborty, PA, Chakraborty, S, Mougin, V, Chan, JSK, Chan, RNC, Chandan, JS, Addo, IY, Chandika, RM, Chaturvedi, P, Chen, A-T, Chen, CS, Chen, H, Chen, MX, Mousavi, P, Chen, M, Chen, S, Cheng, C-Y, Cheng, ETW, Addolorato, G, Cherbuin, N, Chi, G, Chichagi, F, Chimed-Ochir, O, Chimoriya, R, Msherghi, A, Ching, PR, Chirinos-Caceres, JL, Chitheer, A, Cho, WCS, Chong, B, Adedoyin, RA, Chopra, H, Chowdhury, R, Christopher, DJ, Chu, D-T, Mubarik, S, Chukwu, IS, Chung, E, Chung, S-C, Chutiyami, M, Cioffi, I, Cogen, RM, Adekanmbi, V, Cohen, AJ, Columbus, A, Conde, J, Muccioli, L, Corlateanu, A, Cortese, S, Cortesi, PA, Costa, VM, Costanzo, S, Criqui, MH, Cruz, JA, Aden, B, Cruz-Martins, N, Culbreth, GT, Mueller, UO, da Silva, AG, Dadras, O, Dai, X, Dai, Z, Daikwo, PU, Dalli, LL, Damiani, G, D'Amico, E, Adetunji, JB, D'Anna, L, Mulita, F, Darwesh, AM, Das, JK, Das, S, Dash, NR, Dashti, M, Dávila-Cervantes, CA, Davis Weaver, N, Davitoiu, DV, De la Hoz, FP, Adeyeoluwa, TE, Mullany, EC, de la Torre-Luque, A, De Leo, D, Debopadhaya, S, Degenhardt, L, Del Bo', C, Delgado-Enciso, I, Delgado-Saborit, JM, Demoze, CK, Denova-Gutiérrez, E, Dervenis, N, Munjal, K, Adha, R, Dervišević, E, Desai, HD, Desai, R, Devanbu, VGC, Dewan, SMR, Dhali, A, Dhama, K, Dhane, AS, Dhimal, ML, Marx, W, Murillo-Zamora, E, Dhimal, M, Adibi, A, Dhingra, S, Dhulipala, VR, Dhungana, RR, Dias da Silva, D, Diaz, D, Diaz, LA, Diaz, MJ, Dima, A, Abbasi-Kangevari, M, Ding, DD, Dinu, M, Adnani, QES, Djalalinia, S, Do, TC, Do, THP, do Prado, CB, Dodangeh, M, Dohare, S, Dokova, KG, Ali, I, Dong, W, Dongarwar, D, D'Oria, M, Adzigbli, LA, Dorostkar, F, Dorsey, ER, Doshi, R, Doshmangir, L, Dowou, RK, Driscoll, TR, Murlimanju, BV, Dsouza, AC, Dsouza, HL, Dumith, SC, Duncan, BB, Afolabi, AA, Duraes, AR, Duraisamy, S, Dushpanova, A, Dzianach, PA, Dziedzic, AM, Musina, A-M, Ebrahimi, A, Echieh, CP, Ed-Dra, A, Edinur, HA, Edvardsson, D, Afolabi, RF, Edvardsson, K, Efendi, F, Eftekharimehrabad, A, Eini, E, Mustafa, G, Ekholuenetale, M, Ekundayo, TC, El Arab, RA, El Sayed Zaki, M, El-Dahiyat, F, Elemam, NM, Afshin, A, Elgar, FJ, ElGohary, GMT, Elhabashy, HR, Muthu, S, Elhadi, M, Elmehrath, AO, Elmeligy, OAA, Elshaer, M, Elsohaby, I, Emeto, TI, Esfandiari, N, Afyouni, S, Eshrati, B, Eslami, M, Muthupandian, S, Esmaeili, SV, Estep, K, Etaee, F, Fabin, N, Fagbamigbe, AF, Fagbule, OF, Fahimi, S, Falzone, L, Afzal, MS, Fareed, M, Muthusamy, R, Farinha, CSES, Faris, MEM, Faris, PS, Faro, A, Fasina, FO, Fatehizadeh, A, Fauk, NK, Fazylov, T, Feigin, VL, Afzal, S, Muzaffar, M, Feng, X, Fereshtehnejad, S-M, Feroze, AH, Ferrara, P, Ferrari, AJ, Ferreira, N, Fetensa, G, Feyisa, BR, Filip, I, Fischer, F, Maryam, S, Myung, W, Agampodi, SB, Fitriana, I, Flavel, J, Flohr, C, Flood, D, Flor, LS, Foigt, NA, Folayan, MO, Force, LM, Fortuna, D, Nafei, A, Foschi, M, Agbozo, F, Franklin, RC, Freitas, A, Friedman, SD, Fux, B, G, S, Gaal, PA, Gaihre, S, Gajdács, M, Nagarajan, AJ, Galali, Y, Gallus, S, Aghamiri, S, Gandhi, AP, Ganesan, B, Ganiyani, MA, Garcia, V, Gardner, WM, Garg, RK, Gautam, RK, Ali, L, Gebi, TG, Gebregergis, MW, Gebrehiwot, M, Agodi, A, Gebremariam, TBB, Gebremeskel, TG, Gerema, U, Getacher, L, Getahun, GKA, Getie, M, Nagaraju, SP, Ghadirian, F, Ghafarian, S, Ghaffari Jolfayi, A, Ghailan, KY, Agrawal, A, Ghajar, A, Ghasemi, M, Ghasempour Dabaghi, G, Ghasemzadeh, A, Ghassemi, F, Nagel, G, Ghazy, RM, Gholami, A, Gholamrezanezhad, A, Gholizadeh, N, Ghorbani, M, Agyemang-Duah, W, Gil, AU, Gil, GF, Gilbertson, NM, Gill, PS, Naghavi, M, Gill, TK, Gindaba, EZ, Girmay, A, Glasbey, JC, Gnedovskaya, EV, Göbölös, L, Ahinkorah, BO, Godinho, MA, Goel, A, Golechha, M, Naghavi, P, Goleij, P, Golinelli, D, Gomes, NGM, Gopalani, SV, Gorini, G, Goudarzi, H, Goulart, AC, Ahmad, A, Gouravani, M, Goyal, A, Naik, GR, Graham, SM, Grivna, M, Grosso, G, Guan, S-Y, Guarducci, G, Gubari, MIM, Guha, A, Guicciardi, S, Ahmad, D, Gulati, S, Naik, G, Gulisashvili, D, Gunawardane, DA, Guo, C, Gupta, AK, Gupta, B, Gupta, M, Gupta, R, Gupta, RD, Ahmad, F, Mathangasinghe, Y, Nainu, F, Gupta, S, Gupta, VB, Gupta, VK, Habibzadeh, F, Habibzadeh, P, Hadaro, TS, Hadian, Z, Haep, N, Haghi-Aminjan, H, Nair, TS, Ahmad, N, Haghmorad, D, Hagins, H, Haile, D, Hailu, A, Hajj Ali, A, Halboub, ES, 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Sanjeev, RK, Sanna, F, Santomauro, DF, Santric-Milicevic, MM, Sarasmita, MA, Saraswathy, SYI, Saravanan, A, Saravi, B, Sarikhani, Y, Sarmiento-Suárez, R, Mestrovic, T, Alzoubi, KH, Sarode, GS, Sarode, SC, Sartorius, B, Sarveazad, A, Sathian, B, Sattin, D, Sawhney, M, Saya, GK, Sayeed, A, Mettananda, KCD, Sayeed, MA, Al-Zyoud, W, Sayyah, M, Schinckus, C, Schmidt, MI, Schuermans, A, Schumacher, AE, Schutte, AE, Schwarzinger, M, Schwebel, DC, Mettananda, S, Schwendicke, F, Selvaraj, S, Amaechi, UA, Semreen, MH, Senthilkumaran, S, Serban, D, Serre, ML, Sethi, Y, Shafie, M, Shah, H, Miazgowski, T, Shah, NS, Shah, PA, Shah, SM, Aman Mohammadi, M, Shahbandi, A, Shaheen, AA, Shahid, S, Shahid, W, Shahsavari, HR, Shahwan, MJ, Al-Habbal, K, Shaikh, MA, Shaikh, SZ, Shalash, AS, Sham, S, Amani, R, Shamim, MA, Shams-Beyranvand, M, Shamshirgaran, MA, Shamsi, MA, Shanawaz, M, Micha, G, Shankar, A, Sharfaei, S, Sharifan, A, Sharifi-Rad, J, Sharma, M, Abdollahi, M, Amiri, S, Sharma, U, Sharma, V, 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GS, Azizi, H, Abegaz, TM, Azzam, AY, Backhaus, IL, Mondello, S, Badar, M, Badiye, AD, Bagga, A, Baghdadi, S, Bagheri, N, Bagherieh, S, Bahrami Taghanaki, P, Bai, R, Abeldaño Zuñiga, RA, Baig, AA, Moni, MA, Baker, JL, Bakkannavar, SM, Balasubramanian, M, Baltatu, OC, Bam, K, Bandyopadhyay, S, Banik, B, Banik, PC, Banke-Thomas, A, Abiodun, O, Moodi Ghalibaf, A, Bansal, H, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, SL, Bärnighausen, TW, Barone-Adesi, F, Barqawi, HJ, Barrero, LH, Barrow, A, Moore, CE, Abiso, TL, Barteit, S, Basharat, Z, Basiru, A, Basso, JD, Bastan, M-M, Basu, S, Batchu, S, Batra, K, Batra, R, Moradi, M, Baune, BT, Aboagye, RG, Bayati, M, Bayileyegn, NS, Beaney, T, Behnoush, AH, Beiranvand, M, Béjot, Y, Bekele, A, Belgaumi, UI, Bell, AW, Bell, ML, Abolhassani, H, Bello, MB, Bello, OO, Belo, L, Beloukas, A, Bendak, S, Bennett, DA, and Bennitt, FB
Published: 2024

12. Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Author: Vollset, SE, Ababneh, HS, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasian, M, Abbastabar, H, Abd Al Magied, AHA, Abd ElHafeez, S, Abdelkader, A, Abdelmasseh, M, Alrousan, SM, Philip, AK, Phillips, MR, Pigeolet, M, Piradov, MA, Pisoni, E, Plotnikov, E, Poddighe, D, Polibin, RV, Poluru, R, Ponkilainen, VT, Al-Sabah, SK, Popovic, DS, Postma, MJ, Pour-Rashidi, A, Prabhu, D, Prada, SI, Pradhan, J, Pradhan, PMS, Prashant, A, Prates, EJS, Priscilla, T, Alsabri, MA, Purnobasuki, H, Purohit, BM, Puvvula, J, Qasim, NH, Qattea, I, Qazi, AS, Qian, G, Rabiee Rad, M, Radhakrishnan, V, Raeisi Shahraki, H, Altaany, Z, Rafferty, Q, Raggi, A, Raggi, C, Raheem, N, Rahim, F, Rahim, MJ, Rahimibarghani, S, Rahman, MMMR, Rahman, M, Rahman, MA, Al-Tammemi, AB, Rahman, T, Rahmani, AM, Rahmanian, M, Rahmanian, N, Rahmati, R, Rahmawaty, S, Raimondo, D, Raja, A, Rajput, P, Ramadan, M, Al-Tawfiq, JA, Ramasamy, SK, Ramazanu, S, Ramteke, PW, Rana, K, Rana, RK, Ranabhat, CL, Rane, A, Rao, CR, Rao, M, Rasella, D, Altirkawi, KA, Rashedi, V, Rashid, AM, Rasouli-Saravani, A, Rastogi, P, Rasul, A, Rathish, D, Rathnaiah Babu, G, Rauniyar, SK, Ravangard, R, Rawaf, DL, Aluh, DO, Rawaf, S, Raza, RZ, Redwan, EMM, Reifels, L, Reitsma, MB, Remuzzi, G, Rengasamy, KRR, Reshmi, B, Resnikoff, S, Restaino, S, Alvis-Guzman, N, Reyes, LF, Rezaei, N, Rezaei, ZS, Rezaeian, M, Rhee, TG, Rickard, J, Robalik, T, Robinson-Oden, HE, Rocha, HAL, Al-Wardat, MS, Rodrigues, M, Rodriguez, JAB, Roever, L, Romadlon, DS, Ronfani, L, Rony, MKK, Roshandel, G, Rotimi, K, Rout, HS, Roy, B, Abd-Elsalam, S, Al-Worafi, YM, Rubagotti, E, Ruela, GDA, Rumisha, SF, Runghien, T, Russo, M, Saad, AMA, Saber, K, Saber-Ayad, MM, Sabet, CJ, Sabour, S, Aly, H, Sachdev, PS, Saddler, A, Sadee, BA, Sadeghi, M, Saeb, MR, Saeed, U, Safi, SZ, Sagar, R, Saghafi, A, Sagoe, D, Alyahya, MS, Sahebkar, A, Sahoo, PM, Sajid, MR, Salam, N, Salamati, P, Salami, AA, Saleh, MA, Salehi, L, Salem, MR, Salemcity, AJ, Alzoubi, KH, Salimi, S, Samadi Kafil, H, Samargandy, S, Samodra, YL, Samy, AM, Sanabria, J, Sanna, F, Santric-Milicevic, MM, Sao Jose, BP, Saraswathy, SYI, Al-Zyoud, W, Saravanan, A, Sarmiento-Suárez, R, Sarode, GS, Sarode, SC, Sartorius, B, Satpathy, M, Sayeed, A, Scarmeas, N, Schaarschmidt, BM, Schinckus, C, Amani, R, Schuermans, A, Schumacher, AE, Schutte, AE, Schwebel, DC, Schwendicke, F, Selvaraj, S, Semreen, MH, Senapati, S, Sengupta, P, Senthilkumaran, S, Ameyaw, EK, Serban, D, Sethi, Y, Seylani, A, Shafie, M, Shah, PA, Shahbandi, A, Shahid, S, Shahid, W, Shahsavari, HR, Shahwan, MJ, Amin, TT, Shaikh, MA, Shalash, AS, Shamekh, A, Shamim, MA, Shanawaz, M, Shankar, A, Shannawaz, M, Sharath, M, Sharfaei, S, Sharifan, A, Amindarolzarbi, A, Sharifi-Rad, J, Sharma, A, Sharma, M, Sharma, S, Sharma, V, Shastry, RP, Shayan, M, Shekhar, S, Shenoy, RR, Shetty, M, Amiri, S, Shetty, PH, Shetty, PK, Shi, P, Shiani, A, Shigematsu, M, Shimels, T, Shiri, R, Shittu, A, Shiue, I, Shivakumar, KM, Abdi, P, Amirzade-Iranaq, MH, Shool, S, Shorofi, SA, Shrestha, S, Shuval, K, Si, Y, Siddig, EE, Sidhu, JK, Silva, JP, Silva, LMLR, Silva, S, Amu, H, Silva, TPR, Simpson, CR, Simpson, KE, Singh, A, Singh, BB, Singh, B, Singh, H, Singh, J, Singh, P, Amugsi, DA, Skou, ST, Smith, G, Sobia, F, Socea, B, Solanki, S, Soleimani, H, Soliman, SSM, Song, Y, Soyiri, IN, Spartalis, M, Ancuceanu, R, Spearman, S, Sreeramareddy, CT, Stanaway, JD, Stanikzai, MH, Starodubova, AV, Stein, DJ, Steiner, C, Steiropoulos, P, Stockfelt, L, Stokes, MA, Anderlini, D, Straif, K, Subedi, N, Suliankatchi Abdulkader, R, Sultana, A, Sun, J, Sundström, J, Swain, CK, Szarpak, L, Szeto, MD, Tabaee Damavandi, P, Anderson, DB, Tabarés-Seisdedos, R, Tabatabaei Malazy, O, Tabatabaeizadeh, S-A, Tabatabai, S, Tabb, KM, Tabche, C, Tabish, M, Taheri Abkenar, Y, Taheri Soodejani, M, Taiba, J, Andrade, PP, Talaat, IM, Tamuzi, JL, Tan, K-K, Tang, H, Tat, NY, Tavakoli Oliaee, R, Tavangar, SM, Taveira, N, Tbakhi, A, Tehrani, H, Andrei, CL, Temsah, M-H, Teramoto, M, Tesfaye, BT, Teye-Kwadjo, E, Thangaraju, P, Thankappan, KR, Thapar, R, Thayakaran, R, Thirunavukkarasu, S, Thomas, N, Andrei, T, Thygesen, LC, Ticoalu, JHV, Timalsena, D, Tiruye, TY, Tiwari, K, Tomo, S, Tonelli, M, Topor-Madry, R, Touvier, M, Tovani-Palone, MR, Andrews, EA, Tran, AT, Tran, JT, Tran, NM, Tran, TH, Trico, D, Tromans, SJ, Truyen, TTTT, Tsatsakis, A, Tsermpini, EE, Tumurkhuu, M, Abdollahi, M, Anil, A, Turnock, ST, Udoh, A, Ullah, A, Ullah, S, Umakanthan, S, Umar, M, Umar, SS, Unim, B, Unnikrishnan, B, Anil, S, Upadhyay, E, Usman, JS, Vahdati, S, Vaithinathan, AG, Vakili, O, Valizadeh, R, Van den Eynde, J, Vart, P, Varthya, SB, Vasankari, TJ, Anoushiravani, A, Vasic, M, Venketasubramanian, N, Veroux, M, Verras, G-I, Vervoort, D, Vijayageetha, M, Villafañe, JH, Vinayak, M, Violante, FS, Vladimirov, SK, Antony, CM, Vlassov, V, Vo, B, Vohra, K, Vos, T, Wadood, AW, Waheed, Y, Wang, F, Wang, S, Wang, Y, Antriyandarti, E, Wang, Y-P, Wanjau, MN, Waqas, M, Ward, P, 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Golinelli, D, Gopalani, SV, Goulart, AC, Ahmad, F, Gouravani, M, Goyal, A, Grivna, M, Grosso, G, Guarducci, G, Gubari, MIM, Guicciardi, S, Guimarães, RA, Gulati, S, Gulisashvili, D, Ahmad, MM, Gunawardane, DA, Guo, C, Gupta, AK, Gupta, R, Gupta, S, Gupta, VK, Haakenstad, A, Hadi, NR, Ahmad, S, Haep, N, Hafiz, A, Haghmorad, D, Haile, D, Hajj Ali, A, Haj-Mirzaian, A, Halboub, ES, Haller, S, Halwani, R, Hamagharib Abdullah, K, Hamdy, NM, Hamoudi, R, Hanifi, N, Hankey, GJ, Haq, ZA, Haque, MR, Harapan, H, Hargono, A, Haro, JM, Ahmed, A, Hasaballah, AI, Hasan, SMM, Hasanian, M, Hasnain, MS, Hassan, A, Haubold, J, Hay, SI, Hebert, JJ, Hegazi, OE, Heidari, M, Hemmati, M, Henson, CA, Herrera-Serna, BY, Herteliu, C, Heydari, M, Hezam, K, Hidayana, I, Hiraike, Y, Hoan, NQ, Holla, R, Ahmed, H, Hoogar, P, Horita, N, Hossain, MM, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hu, C, Huang, J, Hultström, M, Ahmed, S, Hundie, TG, Hunt, AJ, Hushmandi, K, Hussain, J, Hussain, MA, Hussein, NR, Huynh, H-H, Hwang, B-F, Ibitoye, SE, Iftikhar, PM, Ahmed, SA, Ikiroma, AI, Ikwegbue, PC, Ilic, IM, Ilic, MD, Immurana, M, Isa, MA, Islam, MR, Islam, SMS, Ismail, F, Ismail, NE, Akinosoglou, K, Isola, G, Iwagami, M, Iyamu, IO, Jacob, L, Jacobsen, KH, Jafarinia, M, Jahankhani, K, Jahanmehr, N, Jain, N, Jairoun, AA, Akkaif, MA, Jakhmola Mani, DR, Jamil, S, Jamora, RDG, Jatau, AI, Javadov, S, Javaheri, T, Jayaram, S, Jee, SH, Jeganathan, J, Jiang, H, Akrami, AE, Jokar, M, Jonas, JB, Joseph, N, Joshua, CE, Jürisson, M, K, V, Kabir, A, Kabir, Z, Kadashetti, V, Kalankesh, LR, Akter, E, Kalra, S, Kamath, A, Kamath, R, Kamireddy, A, Kanaan, M, Kanchan, T, Kanmiki, EW, Kanmodi, KK, Kansal, SK, Karim, A, Al Awaidy, S, Karkhah, S, Kashoo, FZ, Kasraei, H, Kassel, MB, Katikireddi, SV, Kauppila, JH, Kaur, H, Kayode, GA, Kazemi, F, Kazemian, S, Al Hasan, SM, Kebede, F, Kendal, ES, Kesse-Guyot, E, Khademvatan, S, Khajuria, H, Khalaji, A, Khalid, A, Khalid, N, Khalilian, A, Khamesipour, F, Al Mosa, AS, Khan, F, Khan, MJ, Khan, MAB, Khanmohammadi, S, Khatab, K, Khatatbeh, H, Khatatbeh, MM, Khatib, MN, Khayat Kashani, HR, Kheirallah, KA, Al Ta'ani, O, Khokhar, M, Khormali, M, Khorrami, Z, Khosla, AA, Khosravi, M, Khosrowjerdi, M, Khubchandani, J, Kifle, ZD, Kim, G, Kim, JS, Al Zaabi, OAM, Kim, MS, Kim, YJ, Kimokoti, RW, Kisa, A, Kisa, S, Knibbs, LD, Knudsen, AKS, Kochhar, S, Kolahi, A-A, Kompani, F, Alahdab, F, Koren, G, Korzh, O, Krishan, K, Krishna, V, Krishnamoorthy, V, Kucuk Bicer, B, Kuddus, MA, Kuddus, M, Kuitunen, I, Kujan, O, Alajlani, MM, Kulimbet, M, Kulkarni, V, Kumar, GA, Kumar, H, Kumar, N, Kumar, R, Kumar, V, Kundu, A, Kusuma, D, Kyei-Arthur, F, Al-Ajlouni, Y, Kytö, V, Kyu, HH, La Vecchia, C, Lacey, B, Ladan, MA, Laflamme, L, Lahariya, C, Lai, DTC, Lalloo, R, Lallukka, T, Alalalmeh, SO, Lám, J, Lan, Q, Lan, T, Landires, I, Lanfranchi, F, Langguth, B, Lansingh, VC, Laplante-Lévesque, A, Larijani, B, Larsson, AO, Al-Aly, Z, Lasrado, S, Lauriola, P, Lawlor, HR, Le, H-H, Le, LKD, Le, NHH, Le, TTT, Le, TDT, Leasher, JL, Lee, DW, Alam, K, Lee, M, Lee, PH, Lee, S-W, Lee, SW, Lee, SWH, Lee, YH, Leigh, J, Leong, E, Li, M-C, Libra, M, Alam, N, Ligade, VS, Lim, L-L, Lim, SS, Limenh, LW, Lindholm, D, Lindstedt, PA, Listl, S, Liu, G, Liu, S, Alam, T, Liu, X, Llanaj, E, López-Bueno, R, López-Gil, JF, Loreche, AM, Lotufo, PA, Lozano, R, Lubinda, J, Lucchetti, G, Alam, Z, Luo, L, Lusk, JB, Lv, L, M Amin, HI, Ma, ZF, Maass, KL, Machairas, N, Machoy, M, Madureira-Carvalho, ÁM, Magdy Abd El Razek, H, Al-amer, RM, Maghazachi, AA, Mahadeshwara Prasad, DR, Mahalleh, M, Mahasha, PW, Mahmoud, MA, Mahmoudi, E, Mahmoudvand, G, Makama, M, Malakan Rad, E, Malhotra, K, Alanezi, FM, Malik, AA, Malta, DC, Manla, Y, Mansour, A, Mansouri, MH, Mansouri, P, Mansouri, V, Mansourian, M, Mansournia, MA, Marasini, BP, Alanzi, TM, Marateb, HR, Maravilla, JC, Mardi, P, Marjani, A, Markazi Moghadam, H, Marrugo Arnedo, CA, Martinez, G, Martinez-Piedra, R, Martins-Melo, FR, Martorell, M, Albakri, A, Marx, W, Marzo, RR, Masoudi, S, Mathangasinghe, Y, Mathioudakis, AG, Mathur, M, Mathur, N, Matozinhos, FP, Mattumpuram, J, Aldhaleei, WA, Maude, RJ, Maugeri, A, Mayeli, M, Mazidi, M, Mazzotti, A, McGrath, JJ, McKee, M, McKowen, ALW, McPhail, MA, McPhail, SM, Aldridge, RW, Mehmood, A, Mehrabani-Zeinabad, K, Mehravar, S, Mekene Meto, T, Melese, EB, Mendez-Lopez, MAM, Mendoza, W, Menezes, RG, Mensah, GA, Mensah, LG, Alemohammad, SY, Mentis, A-FA, Meo, SA, Meretoja, A, Meretoja, TJ, Mersha, AM, Mestrovic, T, Mettananda, KCD, Mettananda, S, Mhlanga, A, Mhlanga, L, Alemu, YM, Miazgowski, T, Michalek, IM, Micheletti Gomide Nogueira de Sá, AC, Miller, TR, Minh, LHN, Mirahmadi, A, Mirijello, A, Mirrakhimov, EM, Mirzaei, R, Mitchell, PB, Al-Gheethi, AAS, Mittal, C, Moberg, ME, Moghadam Fard, A, Mohajelin, S, Mohamadkhani, A, Mohamed, AI, Mohamed, J, Mohamed, MFH, Mohamed, NS, Mohammad, AM, Al-Hanawi, MK, Mohammadi, S, Mohammed, H, Mohammed, M, Mohammed, S, Mokdad, AH, Molokhia, M, Momani, SM, Momtazmanesh, S, Monasta, L, Mondello, S, Ali, A, Moni, MA, Montazeri, F, Moodi Ghalibaf, A, Moradi, M, Moradi, Y, Moraga, P, Morawska, L, Moreira, RS, Morovatdar, N, Morrison, SD, Mosapour, A, Mosser, JF, Mossialos, E, Motappa, R, Mougin, V, Mousavi, P, Mrejen, M, Mubarik, S, Mueller, UO, Mulita, F, Ali, I, Munjal, K, Murillo-Zamora, E, Musallam, KM, Musina, A-M, Mustafa, G, Myung, W, Nafei, A, Nagarajan, AJ, Naghavi, P, Naik, GR, Ali, MU, Naik, G, Nainu, F, Najdaghi, S, Nakhostin Ansari, N, Nangia, V, Narasimha Swamy, S, Nargus, S, Narimani Davani, D, Nascimento, BR, Nascimento, GG, Ali, R, Naser, AY, Nashwan, AJ, Natto, ZS, Nauman, J, Navaratna, SNK, Naveed, M, Nawsherwan, Nayak, BP, Nayak, VC, Negash, H, Ali, SSS, Negoi, I, Negoi, RI, Nejadghaderi, SA, Nejjari, C, Nematollahi, S, Netsere, HB, Ng, M, Nguefack-Tsague, G, Ngunjiri, JW, Nguyen, AH, Ali, VE, Nguyen, DH, Nguyen, HTH, Nguyen, N, Nguyen, NNY, Nguyen, PT, Nguyen, QP, Nguyen, VT, Nguyen Tran Minh, D, Niazi, RK, Ali, W, Nigatu, YT, Niknam, M, Nikoobar, A, Nikpoor, AR, Nikravangolsefid, N, Noman, EA, Nomura, S, Noor, STA, Noroozi, N, Nouri, M, Al-Ibraheem, A, Nozari, M, Nri-Ezedi, CA, Ntaios, G, Nunemo, MH, Nurrika, D, Nutor, JJ, Nzoputam, CI, Nzoputam, OJ, Oancea, B, Obamiro, KO, Alicandro, G, Odetokun, IA, Oduro, MS, Ogundijo, OA, Ogunfowokan, AA, Ogunkoya, A, Oguntade, AS, Oh, I-H, Ojo-Akosile, TR, Okati-Aliabad, H, Okekunle, AP, Alif, SM, Okonji, OC, Olagunju, AT, Olatubi, MI, Oliveira, GMM, Olusanya, BO, Olusanya, JO, Oluwafemi, YD, Omar, HA, Omer, GL, Ong, S, Aljunid, SM, Onie, S, Onwujekwe, OE, Opejin, AO, Ordak, M, Orish, VN, Ortiz, A, Ortiz-Prado, E, Osman, WMS, Ostojic, SM, Ostroff, SM, Alla, F, Osuagwu, UL, Otoiu, A, Otstavnov, SS, Ouyahia, A, Owolabi, MO, Oyeyemi, OT, Ozair, A, P A, MP, Padron-Monedero, A, Padubidri, JR, Almazan, JU, Pal, PK, Palicz, T, Pan, F, Pan, H-F, Panda-Jonas, S, Pandey, A, Pando-Robles, V, Pangaribuan, HU, Panos, GD, Panos, LD, Al-Mekhlafi, HM, Pantazopoulos, I, Pantea Stoian, AM, Parikh, RR, Park, E-K, Park, S, Parsons, N, Parthasarathi, A, Pasovic, M, Passera, R, Alqutaibi, AY, Patel, J, Pathan, AR, Patil, S, Patoulias, D, Pawar, S, Pazoki Toroudi, H, Pease, SA, Peden, AE, Pedersini, P, Pensato, U, Alrawashdeh, A, Pepito, VCF, Peprah, P, Pereira, M, Pereira, MO, Perianayagam, A, Perico, N, Perna, S, Pesudovs, K, Petermann-Rocha, FE, and Pham, HT
Published: 2024

13. DeforestVis: Behaviour Analysis of Machine Learning Models with Surrogate Decision Stumps

Author: Chatzimparmpas, A, Martins, RM, Telea, AC, Kerren, A, Chatzimparmpas, A, Martins, RM, Telea, AC, and Kerren, A
Abstract: As the complexity of machine learning (ML) models increases and their application in different (and critical) domains grows, there is a strong demand for more interpretable and trustworthy ML. A direct, model-agnostic, way to interpret such models is to train surrogate models—such as rule sets and decision trees—that sufficiently approximate the original ones while being simpler and easier-to-explain. Yet, rule sets can become very lengthy, with many if–else statements, and decision tree depth grows rapidly when accurately emulating complex ML models. In such cases, both approaches can fail to meet their core goal—providing users with model interpretability. To tackle this, we propose DeforestVis, a visual analytics tool that offers summarization of the behaviour of complex ML models by providing surrogate decision stumps (one-level decision trees) generated with the Adaptive Boosting (AdaBoost) technique. DeforestVis helps users to explore the complexity versus fidelity trade-off by incrementally generating more stumps, creating attribute-based explanations with weighted stumps to justify decision making, and analysing the impact of rule overriding on training instance allocation between one or more stumps. An independent test set allows users to monitor the effectiveness of manual rule changes and form hypotheses based on case-by-case analyses. We show the applicability and usefulness of DeforestVis with two use cases and expert interviews with data analysts and model developers.
Published: 2024

14. Protocol for spatial prediction of soil transmitted helminth prevalence in the Western Pacific region using a meta-analytical approach

Author: Gilmour, B, Wangdi, K, Restrepo, AC, Tsheten, T, Kelly, M, Clements, A, Gray, D, Lau, C, Espino, FE, Daga, C, Mapalo, V, Nashkova, S, Bartlett, A ; https://orcid.org/0000-0002-7532-9316, Gebreyohannes, EA, Alene, KA, Vaz Nery, Susana ; https://orcid.org/0000-0002-2399-7785, Gilmour, B, Wangdi, K, Restrepo, AC, Tsheten, T, Kelly, M, Clements, A, Gray, D, Lau, C, Espino, FE, Daga, C, Mapalo, V, Nashkova, S, Bartlett, A ; https://orcid.org/0000-0002-7532-9316, Gebreyohannes, EA, Alene, KA, and Vaz Nery, Susana ; https://orcid.org/0000-0002-2399-7785
Abstract: Background: Soil transmitted helminth (STH) infections are estimated to impact 24% of the world’s population and are responsible for chronic and debilitating morbidity. Disadvantaged communities are among the worst affected and are further marginalized as infection prevalence fuels the poverty cycle. Ambitious targets have been set to eliminate STH infections, but accurate epidemiological data will be required to inform appropriate interventions. This paper details the protocol for an analysis that aims to produce spatial prediction mapping of STH prevalence in the Western Pacific Region (WPR). Methods: The protocol follows the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol (PRISMA-P) guidelines. The study design will combine the principles of systematic review, meta-analysis, and geospatial analysis. Systematic searches will be undertaken in PubMed, Scopus, ProQuest, Embase, and Web of Science for studies undertaken post 2000, to identify surveys that enable the prevalence of human STH infection within the WPR to be calculated. Covariate data for multivariable analysis will be obtained from publicly accessible sources. Survey data will be geolocated, and STH prevalence and covariates will be linked to produce a spatially referenced dataset for analysis. Bayesian model-based geostatistics will be used to generate spatially continuous estimates of STH prevalence mapped to a resolution of 1 km2. A separate geospatial model will be constructed for each STH species. Predictions of prevalence will be made for unsampled locations and maps will be overlaid for each STH species to obtain co-endemicity maps. Discussion: This protocol facilitates study replication and may be applied to other infectious diseases or alternate geographies. Results of the subsequent analysis will identify geographies with high STH prevalence’s and can be used to inform resource allocation in combating this neglected tropical disease. Trial registration: Open Science Fr
Published: 2024

15. Specialised residential care for older people subject to homelessness: experiences of residents and staff of a new aged care home in Australia

Author: Preti, C, Poulos, CJ ; https://orcid.org/0000-0002-3090-3839, Poulos, RG ; https://orcid.org/0000-0002-2505-1870, Reynolds, NL, Rowlands, AC, Flakelar, K, Raguz, A, Valpiani, P, Faux, SG, O’Connor, CMC, O'Connor, Claire ; https://orcid.org/0000-0002-3541-708X, Preti, C, Poulos, CJ ; https://orcid.org/0000-0002-3090-3839, Poulos, RG ; https://orcid.org/0000-0002-2505-1870, Reynolds, NL, Rowlands, AC, Flakelar, K, Raguz, A, Valpiani, P, Faux, SG, O’Connor, CMC, and O'Connor, Claire ; https://orcid.org/0000-0002-3541-708X
Abstract: Background: The number of older people experiencing homelessness in Australia is rising, yet there is a lack of specialised residential care for older people subject to homelessness with high care and palliative needs. To address this significant gap, a purpose-built care home was recently opened in Sydney, Australia. Methods: This qualitative study explores the experiences of both residents and staff who were living and working in the home over the first twelve months since its opening. Residents were interviewed at baseline (n = 32) and after six months (n = 22), while staff (n = 13) were interviewed after twelve months. Interviews were analysed using a reflexive thematic analysis approach informed by grounded theory. Results: Three main themes emerged: (1) Challenges in providing care for older people subject to homelessness with high care needs; (2) Defining a residential care service that supports older people subject to homelessness with high care needs, and (3) Perception of the impact of living and working in a purpose-built care home after six months (residents) and twelve months (staff) since its opening. A key finding was that of the complex interplay between resident dependency and behaviours, referral pathways and stakeholder engagement, government funding models and requirements, staff training and wellbeing, and the need to meet operational viability. Conclusion: This study provides novel insights into how the lives of older people subject to homelessness with high care needs are affected by living in a specifically designed care home, and on some of the challenges faced and solved by staff working in the care home. A significant gap in the healthcare system remains when it comes to the effective provision of high care for older people subject to homelessness.
Published: 2024

16. Complementing model species with model clades

Author: Mabry, ME, Abrahams, RS, Al-Shehbaz, IA, Baker, WJ, Barak, S, Barker, MS, Barrett, RL ; https://orcid.org/0000-0003-0360-8321, Beric, A, Bhattacharya, S, Carey, SB, Conant, GC, Conran, JG, Dassanayake, M, Edger, PP, Hall, JC, Hao, Y, Hendriks, KP, Hibberd, JM, King, GJ, Kliebenstein, DJ, Koch, MA, Leitch, IJ, Lens, F, Lysak, MA, McAlvay, AC, McKibben, MTW, Mercati, F, Moore, RC, Mummenhoff, K, Murphy, DJ, Nikolov, LA, Pisias, M, Roalson, EH, Schranz, ME, Thomas, SK, Yu, Q, Yocca, A, Pires, JC, Harkess, AE, Mabry, ME, Abrahams, RS, Al-Shehbaz, IA, Baker, WJ, Barak, S, Barker, MS, Barrett, RL ; https://orcid.org/0000-0003-0360-8321, Beric, A, Bhattacharya, S, Carey, SB, Conant, GC, Conran, JG, Dassanayake, M, Edger, PP, Hall, JC, Hao, Y, Hendriks, KP, Hibberd, JM, King, GJ, Kliebenstein, DJ, Koch, MA, Leitch, IJ, Lens, F, Lysak, MA, McAlvay, AC, McKibben, MTW, Mercati, F, Moore, RC, Mummenhoff, K, Murphy, DJ, Nikolov, LA, Pisias, M, Roalson, EH, Schranz, ME, Thomas, SK, Yu, Q, Yocca, A, Pires, JC, and Harkess, AE
Abstract: Model species continue to underpin groundbreaking plant science research. At the same time, the phylogenetic resolution of the land plant tree of life continues to improve. The intersection of these 2 research paths creates a unique opportunity to further extend the usefulness of model species across larger taxonomic groups. Here we promote the utility of the Arabidopsis thaliana model species, especially the ability to connect its genetic and functional resources, to species across the entire Brassicales order. We focus on the utility of using genomics and phylogenomics to bridge the evolution and diversification of several traits across the Brassicales to the resources in Arabidopsis, thereby extending scope from a model species by establishing a “model clade.” These Brassicales-wide traits are discussed in the context of both the model species Arabidopsis and the family Brassicaceae. We promote the utility of such a “model clade” and make suggestions for building global networks to support future studies in the model order Brassicales.
Published: 2024

17. Silica from Waste of Fluorine-Derivatives Industry Applied for Microscafs® Synthesis

Author: Montini, D, Cara, C, D'Arienzo, M, Di Credico, B, Mostoni, S, Nisticç, R, Pala, L, Marques, A, Scotti, R, Marques, AC, Montini, D, Cara, C, D'Arienzo, M, Di Credico, B, Mostoni, S, Nisticç, R, Pala, L, Marques, A, Scotti, R, and Marques, AC
Published: 2024

18. Analyzing functional heterogeneity of effector cells for enhanced adoptive cell therapy applications

Author: Kiel Rasmussen, AC C., Hulen, T. M., Petersen, D. L., Jacobsen, M. J., Mikkelsen, M. J., Met, Donia, M., Chamberlain, C. A., Mouritzen, P., Kiel Rasmussen, AC C., Hulen, T. M., Petersen, D. L., Jacobsen, M. J., Mikkelsen, M. J., Met, Donia, M., Chamberlain, C. A., and Mouritzen, P.
Abstract: Cellular effector function assays traditionally rely on bulk cell populations that mask complex heterogeneity and rare subpopulations. The Xdrop® droplet technology facilitates high-throughput compartmentalization of viable single cells or single-cell pairs in double-emulsion droplets, enabling the study of single cells or cell–cell interactions at an individual level. Effector cell molecule secretion and target cell killing can be evaluated independently or in combination. Compatibility with a wide range of commercial assay reagents allows for single-cell level readouts using common laboratory techniques such as flow cytometry or microscopy. Moreover, individual cells of interest can be viably isolated for further investigation or expansion. Here we demonstrate the application of the double-emulsion droplet technology with a range of cell types commonly utilized for adoptive cell therapy of cancer: natural killer cells, blood-derived T cells, tumor-infiltrating lymphocytes, and chimeric antigen receptor T cells. Single-cell compartmentalization offers unparalleled resolution, serving as a valuable tool for advancing the development and understanding of cellular therapy products.
Published: 2024

19. A reproducible, self-reported, field-based tool for monitoring ovarian hormone status and body weight variations in female athletes: the Answ'Her questionnaire

Author: Bagot, S, Pereira, B, Lambert, C, Pelissier, L, Chanseaume, E, Duclos, M, Hackney, AC, Elliott-Sale, KJ, Thivel, D, Isacco, L, Bagot, S, Pereira, B, Lambert, C, Pelissier, L, Chanseaume, E, Duclos, M, Hackney, AC, Elliott-Sale, KJ, Thivel, D, and Isacco, L
Abstract: BACKGROUND: Intra-individual factors like ovarian hormone profiles and body weight variations may influence sports practice and performance in female athletes and need to be characterized. The "Answ'Her"questionnaire was designed to develop a relevant and reproducible fieldbased tool to assess self-reported ovarian hormone status (natural menstrual cycle and hormonal contraceptive use) and body weight variations practices among female athletes. METHODS: French females with a regular sports practice responded (once: N.=210; twice: N.=86; thrice: N.=66) to this 73-item questionnaire reporting their ovarian hormone status, associated symptoms, perceived influence on sports practice, and body weight variations. Reproducibility was evaluated, then a descriptive cross-sectional analysis was conducted on athletes. RESULTS: Reproducibility was verified with 92% of Lin's correlation concordance coefficients above 0.7 and 100% of weighted agreements above 70%. Ultimately 185 female athletes (23.0±4.8 years) were included in the cross-sectional analysis. Whether they used hormonal contraceptive (46.5%) or not (53.5%), most of the athletes perceived a negative impact of their ovarian hormone status on sports practice (78.7%) and performance (84.7%). Overall, 77.3% of the athletes had experienced body weight variations that were significantly associated with an interruption of menses (>3 months) and menses irregularity over the last three years. CONCLUSIONS: The Answ'Her questionnaire is a simple and effective reproducible field-based tool for the self-reported characterisation of female athlete ovarian hormone status and body weight variations. It could be used for a unique and simple overview of the athlete situation but also in a longitudinal design to assess the athlete's evolution and/or effectiveness of implanted training strategies.
Published: 2024

20. HIV, HIV-specific Factors and Myocardial Disease in Women

Author: Kato, Yoko, Kato, Yoko, Ambale-Venkatesh, Bharath, Naveed, Mahim, Shitole, Sanyog G, Peng, Qi, Levsky, Jeffrey M, Haramati, Linda B, Ordovas, Karen, Noworolski, Susan M, Lee, Yoo Jin, Kim, Ryung S, Lazar, Jason M, Anastos, Kathryn, Tien, Phyllis C, Kaplan, Robert C, Lima, Joao AC, Kizer, Jorge R, Kato, Yoko, Kato, Yoko, Ambale-Venkatesh, Bharath, Naveed, Mahim, Shitole, Sanyog G, Peng, Qi, Levsky, Jeffrey M, Haramati, Linda B, Ordovas, Karen, Noworolski, Susan M, Lee, Yoo Jin, Kim, Ryung S, Lazar, Jason M, Anastos, Kathryn, Tien, Phyllis C, Kaplan, Robert C, Lima, Joao AC, and Kizer, Jorge R
Published: 2024

21. Introducing CRC SAAFE: a new Cooperative Research Centre (CRC) focused on managing AMR in agriculture and the environment

Author: Donner, E, Magalhães, RJS, Barnes, AC, Jex, A, Jarocki, V, Drigo, B, Djordjevic, S, Ashbolt, NJ, Donner, E, Magalhães, RJS, Barnes, AC, Jex, A, Jarocki, V, Drigo, B, Djordjevic, S, and Ashbolt, NJ
Abstract: Antimicrobial resistance (AMR) is a complex challenge that poses a critical threat to food and water safety and security as well as to human, animal and environmental health. It is projected to cost the global economy US$100 trillion by 2050. Australia’s new Cooperative Research Centre (CRC) for Solving Antimicrobial Resistance in Agribusiness, Food and Environments (SAAFE) is part of Australia’s One Health approach to mitigating AMR. SAAFE’s 10-year, A$150-million industry-led program will help protect Australia’s food and agribusiness industries, and the environments in which they operate, from the growing threat of AMR. Through its research programs, CRC SAAFE uses a partner-based approach to assist industries to monitor, analyse and mitigate AMR, with projects spanning horticulture, viticulture, aquaculture, animal industries, water and waste.
Published: 2024

22. Retraction Note: Polysaccharide-fecal microbiota-based colon-targeted self-nanoemulsifying drug delivery system of curcumin for treating polycystic ovarian syndrome.

Author: Corrie, L, Singh, H, Gulati, M, Vishwas, S, Chellappan, DK, Gupta, G, Paiva-Santos, AC, Veiga, F, Alotaibi, F, Alam, A, Eri, RD, Prasher, P, Adams, J, Paudel, KR, Dua, K, Singh, SK, Corrie, L, Singh, H, Gulati, M, Vishwas, S, Chellappan, DK, Gupta, G, Paiva-Santos, AC, Veiga, F, Alotaibi, F, Alam, A, Eri, RD, Prasher, P, Adams, J, Paudel, KR, Dua, K, and Singh, SK
Published: 2024

23. Forecasting the effects of smoking prevalence scenarios on years of life lost and life expectancy from 2022 to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Author: Bryazka, D, Reitsma, MB, Abate, YH, Abd Al Magied, AHA, Abdelkader, A, Abdollahi, A, Abdoun, M, Abdulkader, RS, Abeldaño Zuñiga, RA, Abhilash, ES, Abiodun, OO, Andrei, CL, Zhang, L, Zhong, CC, Zhou, SC, Zhu, B, Zielińska, M, Zoghi, G, Zyoud, SH, Vollset, SE, Gakidou, E, Andrei, T, Ansari, MT, Anuoluwa, IA, Anvari, S, Anwar, SL, Anyasodor, AE, Arabloo, J, Arafa, EA, Aravkin, AY, Abiodun, O, Areda, D, Aregawi, BB, Aremu, O, Artamonov, AA, Asgedom, AA, Asghari-Jafarabadi, M, Ashemo, MY, Ashraf, T, Astell-Burt, T, Athari, SS, Aboagye, RG, Atorkey, P, Atreya, A, Aujayeb, A, Awotidebe, AW, Ayano, G, Aychiluhm, SB, Azadnajafabad, S, Azzam, AY, Babu, GR, Bahrami Taghanaki, P, Abreu, LG, Bahramian, S, Bai, R, Bakkannavar, SM, Balakrishnan, S, Bam, K, Banach, M, Bandyopadhyay, S, Baran, MF, Barchitta, M, Bardhan, M, Abtahi, D, Barker-Collo, SL, Barrow, A, Bashiru, HA, Basiru, A, Bastan, M-M, Basu, S, Batra, K, Bayati, M, Behnoush, AH, Abualruz, H, Bell, SL, Belo, L, Beneke, AA, Bennett, DA, Bensenor, IM, Beran, A, Bermudez, ANC, Beyene, HB, Bhagat, DS, Bhagavathula, AS, Abubakar, B, Bhala, N, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bhat, AN, Bhattacharjee, NV, Bhattacharjee, P, Bhatti, JS, Bilgin, C, Biswas, A, Abu-Rmeileh, NME, Biswas, B, Boachie, MK, Bogale, EK, Bora Basara, B, Borhany, H, Bosoka, SA, Bouaoud, S, Boyko, EJ, Brenner, H, Brunoni, AR, Aburuz, S, Bugiardini, R, Bulamu, NB, Bustanji, Y, Butt, ZA, Caetano dos Santos, FL, Calina, D, Cao, C, Cao, F, Capodici, A, Cárdenas, R, Abu-Zaid, A, Carreras, G, Castaldelli-Maia, JM, Cattaruzza, MS, Caye, A, Cegolon, L, Cenko, E, Cerrai, S, Chakraborty, S, Chandika, RM, Chandrasekar, EK, Adane, MM, Chattu, VK, Chaudhary, AA, Chaurasia, A, Chen, A-T, Chen, G, Chen, H, Chen, MX, Chen, S, Cheng, KJG, Chi, G, Adebiyi, AO, Chichagi, F, Chimoriya, R, Chirinos-Caceres, JL, Chitheer, A, Chong, B, Chong, CL, Chong, YY, Chopra, H, Choudhari, SG, Chu, D-T, Adegboye, OA, Chukwu, IS, Chung, S-C, Chutiyami, M, Conde, J, Corlateanu, A, Criqui, MH, Cruz-Martins, N, da Silva, AG, Dadras, O, Dai, S, Adekanmbi, V, Dai, X, Damiani, G, Dandona, L, Dandona, R, Darcho, SD, Darvishi Cheshmeh Soltani, R, Das, S, Dash, NR, Davletov, K, Debele, AT, Adewuyi, HO, Debopadhaya, S, Demant, D, Desai, HD, Devegowda, D, Dewan, SMR, Dhali, A, Dhane, AS, Dhulipala, VR, Do, TC, Dodangeh, M, Adnani, QES, Doegah, PT, Dohare, S, Dongarwar, D, D'Oria, M, Doshi, OP, Doshi, RP, Dowou, RK, Dsouza, AC, Dsouza, HL, Dsouza, VS, Adzigbli, LA, Duncan, BB, Duraes, AR, Dziedzic, AM, E'mar, AR, Ebrahimi, A, Ebrahimi, N, Ebrahimi Kalan, M, Edvardsson, D, Edvardsson, K, Efendi, F, Afaghi, S, Effendi, DE, Eghbali, F, Ekholuenetale, M, El Arab, RA, El Bayoumy, IF, El Sayed, I, Elbarazi, I, Elhadi, M, El-Huneidi, W, Elmonem, MA, Afolabi, AA, ELNahas, G, Elsohaby, I, Eltaha, C, Eltahir, ME, Emamverdi, M, Emeto, TI, Erku, DA, Etaee, F, Ezenwankwo, EF, Fabin, N, Afzal, MS, Fagbamigbe, AF, Fagbule, OF, Faghani, S, Fahim, A, Fakhradiyev, IR, Falzone, L, Farooque, U, Fatehizadeh, A, Fatima, Z, Fauk, NK, Afzal, S, Fazylov, T, Feizkhah, A, Fekadu, G, Feng, X, Ferrara, P, Ferreira, N, Feyisa, BR, Filippidis, FT, Fischer, F, Flor, LS, Agodi, A, Foigt, NA, Fortuna Rodrigues, C, Foschi, M, G, S, Gaal, PA, Gadanya, MA, Gaidhane, AM, Gajdács, M, Gallus, S, Gandhi, AP, Agyemang-Duah, W, Ganesan, B, Gautam, P, Gautam, RK, Gebregergis, MW, Gebrehiwot, M, Gebremeskel, TG, Getacher, L, Ghadirian, F, Ghazy, RM, Gholamrezanezhad, A, Ahinkorah, BO, Ghorbani, M, Ghozy, S, Gil, AU, Gil, GF, Gnedovskaya, EV, Goel, S, Goharinezhad, S, Goldust, M, Golechha, M, Goleij, P, Ahlstrom, AJ, Golinelli, D, Gorini, G, Gouravani, M, Grada, A, Grivna, M, Grover, S, Guan, S-Y, Gubari, MIM, Guha, A, Guicciardi, S, Ahmad, A, Gulati, S, Gunawardane, DA, Gunturu, S, Guo, Z, Gupta, AK, Gupta, B, Gupta, I, Gupta, M, Gupta, R, Gupta, S, Ahmad, D, Gupta, VB, Gupta, V, Gupta, VK, Hadei, M, Hadi, NR, Hajj Ali, A, Halboub, ES, Hamdy, NM, Hamidi, S, Hammoud, A, Ahmad, MM, Hankey, GJ, Hargono, A, Haro, JM, Hasaballah, AI, Hasan, F, Hasan, MK, Hasnain, MS, Hassan, A, Hassan, II, Hassan, S, Ahmad, S, Hay, SI, Heibati, B, Heidari, M, Hemmati, M, Hendrie, D, Herteliu, C, Heyi, DZ, Hezam, K, Hiraike, Y, Hoan, NQ, Holla, R, Horita, N, Hossain, MM, Hossain, S, Hosseinzadeh, H, Hostiuc, M, Hostiuc, S, Huang, J, Humayun, A, Hussain, J, Ahmadi, A, Hwang, B-F, Ibitoye, SE, Ikeda, N, Ikiroma, A, Ilesanmi, OS, Ilic, IM, Ilic, MD, Immurana, M, Inbaraj, LR, Iqhrammullah, M, Ahmed, A, Irham, LM, Islam, MR, Islam, SMS, Islami, F, Isola, G, Itumalla, R, Iwagami, M, Iyer, M, J, V, Jaafari, J, Jacob, L, Jafarzadeh, A, Jaggi, K, Jahanmehr, N, Jain, A, Jain, N, Jairoun, AA, Jaka, S, Jakovljevic, M, Jalilzadeh Yengejeh, R, Ahmed, H, Jamshidi, E, Janodia, MD, Jawaid, T, Jayapal, SK, Jayaram, S, Jayasinghe, RD, Jebai, R, Jee, SH, Jeswani, BM, Jiang, H, Ahmed, MB, Jokar, M, Jonas, JB, Joo, T, Joseph, N, Joshua, CE, Jozwiak, JJ, Jürisson, M, K, V, Kabir, A, Kabir, Z, Ahmed, S, Kadashetti, V, Kamarajah, SK, Kanaan, M, Kanmodi, KK, Kant, S, Kantar, RS, Karakasis, P, Karaye, IM, Karimi, SE, Karimi, Y, Ajami, M, Karimi Behnagh, A, Karkhah, S, Karki, P, Kashoo, FZ, Katikireddi, SV, Kaur, H, Kaur, N, Kazemian, S, Kazmi, TH, Keiyoro, PN, Akkaif, MA, Kesse-Guyot, E, Khader, YS, Khajuria, H, Khalaji, A, Khalilian, A, Khan, A, Khan, M, Khan, MJ, Khan, MAB, Khanmohammadi, S, Akter, E, Khatab, K, Khatatbeh, H, Khatatbeh, MM, Khater, AM, Kheirallah, KA, Khokhar, M, Khormali, M, Khosla, AA, Khosravi, S, Kim, K, Al Awaidy, S, Kim, MS, Kim, YJ, Kisa, A, Kolahi, A-A, Komaki, S, Kondlahalli, SKMM, Korja, M, Korzh, O, Kosen, S, Kostev, K, Al Hasan, SM, Krishan, K, Kuate Defo, B, Kuddus, M, Kujan, O, Kulimbet, M, Kumar, A, Kumar, GA, Kumar, N, Kumar, R, Kumar, V, Al-Ajlouni, Y, Kundu, A, Kundu, S, Kunutsor, SK, Kurmi, OP, Kusuma, D, Kyei-Arthur, F, Kytö, V, La Vecchia, C, Lahariya, C, Lai, DTC, Al-Aly, Z, Lai, H, Lalloo, R, Lallukka, T, Larijani, B, Lasrado, S, Lau, J, Lauriola, P, Le, TTT, Leasher, JL, Lee, M, Alam, K, Lee, SW, Lee, W-C, Lee, YH, Leong, E, Lerango, TL, Li, A, Li, W, Ligade, VS, Lim, SS, Lin, J, Alam, Z, Lindstedt, PA, Liu, G, Llanaj, E, López-Gil, JF, Lotufo, PA, Lucchetti, G, Lugo, A, Lusk, JB, M Amin, HI, Ma, ZF, Aldhaleei, WA, Machoy, M, Madadizadeh, F, Mahmoudi, E, Makram, AM, Makram, OM, Malhotra, K, Malik, AA, Malta, DC, Mamun, AA, Mansouri, P, Algammal, AM, Mansournia, MA, Manu, E, Marateb, HR, Martinez-Raga, J, Martorell, M, Marzo, RR, Mathangasinghe, Y, Mathews, E, Mathur, M, Mathur, N, Al-Gheethi, AAS, Mattiello, R, Maugeri, A, McKee, M, Mechili, EA, Mehrotra, R, Mekene Meto, T, Mekonnen, BD, Meles, HN, Mendoza, W, Menezes, RG, Alhabib, KF, Meo, SA, Meretoja, A, Meretoja, TJ, Mestrovic, T, Meyers, CCA, Michalek, IM, Miller, TR, Minervini, G, Mirghafourvand, M, Mirrakhimov, EM, Alhalaiqa, FN, Mishra, V, Misra, S, Mithra, P, Mohamed, AI, Mohamed, J, Mohamed, MFH, Mohamed, NS, Mohammad, AM, Mohammad-Alizadeh-Charandabi, S, Mohammadzadeh, I, Al-Hanawi, MK, Mohammed, H, Mohammed, S, Mohan, S, Mokdad, AH, Molavi Vardanjani, H, Molinaro, S, Momani, S, Mondal, H, Mons, U, Moodi Ghalibaf, A, Ali, A, Moradi, M, Moreira, RS, Morovatdar, N, Morrison, SD, Mougin, V, Mukoro, GD, Mulita, F, Mullany, EC, Muniyandi, M, Munkhsaikhan, Y, Ali, MU, Murillo-Zamora, E, Murray, CJL, Myung, W, Naghavi, P, Naik, GR, Najdaghi, S, Najmuldeen, HHR, Naldi, L, Nambi, G, Nangia, V, Ali, R, Nansseu, JR, Nargus, S, Nascimento, GG, Nashwan, AJ, Natto, ZS, Nauman, J, Naveed, M, Nawsherwan, Nayak, BP, Nayak, VC, Ali, SS, Nazri-Panjaki, A, Nduaguba, SO, Negoi, RI, Nejad Shahrokh Abadi, R, Nejadghaderi, SA, Nejjari, C, Neupane, S, Ng, M, Ngunjiri, JW, Nguyen, DH, Ali, W, Nguyen, HTH, Nguyen, HQ, Nguyen, PT, Nguyen, VT, Nigatu, YT, Nikolouzakis, TK, Nikoobar, A, Nikravangolsefid, N, Niranjan, V, Alif, SM, Nnaji, CA, Nnyanzi, LA, Noman, EA, Nomura, S, Noor, STA, Noreen, M, Nozari, M, Nugen, F, Nzoputam, CI, Nzoputam, OJ, Aljunid, SM, Oancea, B, Obamiro, KO, Odetokun, IA, Odo, DBO, Odukoya, OO, Oduro, MS, Oguta, JO, Oh, I-H, Okati-Aliabad, H, Okeke, SR, Alla, F, Okekunle, AP, Okonji, OC, Olagunju, AT, Olasupo, OO, Olatubi, MI, Oliveira, GMM, Olorukooba, AA, Omer, GL, Ong, SK, Opejin, AO, Allebeck, P, Ordak, M, Orish, VN, Ortiz-Prado, E, Osuagwu, UL, Otstavnov, SS, Ouyahia, A, P A, MP, Padron-Monedero, A, Padubidri, JR, Pak, A, Almahmeed, W, Palma-Alvarez, RF, Pan, H-F, Panagiotakos, D, Panda-Jonas, S, Pandey, A, Panos, LD, Pantazopoulos, I, Pantea Stoian, A, Papadopoulou, P, Pardhan, S, Al-Marwani, S, Parija, PP, Parikh, RR, Park, E-K, Park, S, Parsons, N, Passera, R, Patel, J, Patel, SK, Patil, S, Patwary, H, Al-Maweri, S, Pawar, S, Peprah, P, Pereira, G, Perianayagam, A, Pestell, RG, Petermann-Rocha, FE, Pham, T, Philip, AK, Phillips, MR, Poddighe, D, Alomari, MA, Polibin, RV, Poluru, R, Porru, F, Pourshams, A, Pradhan, J, Pradhan, PMS, Prasad, M, Prashant, A, Prates, EJS, Pribadi, DRA, Alqahtani, JS, Purohit, BM, Puvvula, J, Qattea, I, Radhakrishnan, V, Raggi, C, Raghav, P, Rahim, F, Rahimi-Movaghar, A, Rahman, MM, Rahman, M, Alqutaibi, AY, Rahman, MA, Rahmani, S, Rahmanian, M, Rahmanian, N, Rajendran, V, Rajpoot, PL, Rajput, P, Ram, P, Ramadan, MM, Ramadan, M, Al-Raddadi, RMM, Rana, K, Rana, RK, Ranabhat, CL, Rao, SJ, Rashedi, S, Rashid, AM, Rashidi, M-M, Rasouli-Saravani, A, Rathish, D, Rauniyar, SK, Alrousan, SM, Rautalin, I, Ravikumar, N, Rawaf, S, Reddy, MMRK, Redwan, EMM, Rezaei, N, Rezaeian, M, Riad, A, Rodrigues, M, Rodrigues da Silva, TPR, Alsakarneh, S, Rodriguez, JAB, Roever, L, Root, KT, Roshandel, G, Ross, AG, Rout, HS, Roy, B, Roy, N, Roy, S, Ruela, GDA, Alshahrani, NZ, S N, C, Sabet, CJ, Sabour, S, Sadarangani, KP, Saddik, BA, Sadeghi, M, Saeb, MR, Saeed, U, Saeedi, P, Safi, SZ, Altaany, Z, Sagoe, D, Saheb Sharif-Askari, F, Sahebkar, A, Sahoo, SS, Sajib, MRUZ, Sajid, MR, Salaroli, LB, Saleh, MA, Salem, MZY, Salihu, D, Altaf, A, Samodra, YL, Samy, AM, Sanabria, J, 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M, Shafiee, A, Shahbandi, A, Shahid, S, Shahsavari, HR, Shahwan, MJ, Shaikh, A, Shaikh, MA, Aly, H, Shalash, AS, Shamim, MA, Shamsi, A, Shamsutdinova, A, Shanawaz, M, Shankar, A, Shannawaz, M, Sharath, M, Sharifan, A, Sharma, M, Aly, S, Sharma, U, Sharma, V, Sheikh, A, Sheikhy, A, Shetty, M, Shetty, PH, Shetty, PK, Shiferaw, D, Shimels, T, Shiri, R, Alyahya, MSI, Shittu, A, Shiue, I, Shivarov, V, Shorofi, SA, Shrestha, S, Siddig, EE, Silva, JP, Singh, A, Singh, B, Singh, H, Alzoubi, KH, Singh, JA, Singh, P, Singh, S, Singh, V, Sitas, F, Smith, AE, Soboka, M, Solanki, R, Solmi, M, Al-Zyoud, WA, Soraneh, S, Soriano, JB, Soyiri, IN, Spartalis, M, Sreeramareddy, CT, Stachteas, P, Stein, DJ, Steiropoulos, P, Stevanović, A, Straif, K, Amani, R, Suleman, M, Sulo, G, Sun, Z, Suresh, V, Swain, CK, Szarpak, L, T Y, SS, Tabaee Damavandi, P, Tabatabaei Malazy, O, Tabatabaeizadeh, S-A, Amin, TT, Tabche, C, Tadakamadla, J, Tadakamadla, SK, Taiba, J, Talaat, IM, Talukder, A, Tampa, M, Tamuzi, JLJL, Tan, K-K, Tareke, M, Amiri, S, Tarigan, IU, Teimoori, M, Temsah, M-H, Temsah, RMH, Teramoto, M, Terefa, DR, Thangaraju, P, Thankappan, KR, Thapar, R, Thayakaran, R, Amu, H, Thomas, NK, Ticoalu, JHV, Tiwari, K, Topor-Madry, R, Tovani-Palone, MR, Trabelsi, K, Tran, AT, Tran, NH, Tran, TH, Tran Minh Duc, N, Amul, GGH, Trihandini, I, Tripathy, JP, Truyen, TTTT, Tsermpini, EE, Tualeka, AR, Udoakang, AJ, Udoh, A, Ullah, A, Ullah, S, Umair, M, Amusa, GA, Unim, B, Unnikrishnan, B, Usman, JS, Vahdati, S, Vaithinathan, AG, Van den Eynde, J, Vardavas, C, Vasankari, TJ, Vaziri, S, Vellingiri, B, Anand, T, Venketasubramanian, N, Verma, M, Villeneuve, PJ, Vinayak, M, Violante, FS, Vladimirov, SK, Volovat, SR, Wadood, A, Waheed, Y, Walde, MT, Anderlini, D, Wang, S, Wang, Y, Waqas, M, Wickramasinghe, ND, Willeit, P, Wojewodzic, MW, Wolde, AA, Wonde, TE, Xiao, H, Xu, S, Anderson, DB, Yadav, MK, Yamagishi, K, Yang, D, Yang, L, Yano, Y, Yarahmadi, A, Yesodharan, R, Yezli, S, Yi, X, Yiğit, A, Anderson, JA, Yin, D, Yon, DK, Yonemoto, N, Yoon, S-J, Yu, C, Yuan, C-W, Zakham, F, Zeariya, MGM, Zhang, H, and Zhang, J
Published: 2024

24. Mentha aquatica (Water Mint) as a Source of Active Pharmaceutical and Cosmetic Ingredients: A Critical Review.

Author: Pires, PC, Motallebi, M, Marques, MP, Correia, M, Sharma, A, Damiri, F, Hameed, H, Singh, SK, Dua, K, Jha, NK, Cabral, C, Veiga, F, Paiva-Santos, AC, Pires, PC, Motallebi, M, Marques, MP, Correia, M, Sharma, A, Damiri, F, Hameed, H, Singh, SK, Dua, K, Jha, NK, Cabral, C, Veiga, F, and Paiva-Santos, AC
Abstract: Mentha aquatica L., or water mint, is an important member of the Mentha genus, and has long been used in traditional medicine, mainly to treat respiratory diseases such as the common cold. Nevertheless, although over the years many studies have shown that it's potential grows beyond this use, a review that highlights M. aquatica L.'s true potential is still lacking. Thus, the main purpose of the present article is to provide a thorough and multidisciplinary critical review of M. aquatica L., including its phytochemical characterization, main bioactivities, and current marketed cosmetic products. Many compounds have been identified as part of M. aquatica L. composition, such as terpenes, phenolic acids, phenols, and terpenoids, which have been linked to a vast therapeutic potential, namely anti-inflammatory, antioxidant, antibacterial, antifungal, antiobesity, and hepatoprotection bioactivities, with additional anticancer potential for several types of tumors (breast, lung, and skin), and psycho and neuroactive potential in depression, or Alzheimer's or Parkinson's disease. Additionally, it has been proven to be suitable for cosmetic application since several cleansing, hydrating, protecting, and/or odor masking products containing it are already available, with the main functions attributed to M. aquatica including refreshing/cooling effects, calming/soothing/relaxing effects, and purifying effects, properties closely related to its anti-inflammatory and antioxidant bioactivities. Hence, M. aquatica is an extremely versatile plant, with its extracts and essential oils having great therapeutic and cosmetic potential. With many marketed cosmetic products, future studies should focus on this plant's medicinal aspects, so that 1 day it can be part of therapeutic regimens.
Published: 2024

25. Activated non-neuronal cholinergic system correlates with non-type 2 inflammation and exacerbations in severe asthma.

Author: Huang, D, Zhang, L, Liu, Y, Wang, J, Zhang, J, Baines, KJ, Liu, G, Hsu, AC-Y, Wang, F, Chen, Z, Oliver, BG, Xie, M, Qin, L, Liu, D, Wan, H, Luo, F, Li, W, Wang, G, Gibson, PG, Huang, D, Zhang, L, Liu, Y, Wang, J, Zhang, J, Baines, KJ, Liu, G, Hsu, AC-Y, Wang, F, Chen, Z, Oliver, BG, Xie, M, Qin, L, Liu, D, Wan, H, Luo, F, Li, W, Wang, G, and Gibson, PG
Abstract: BACKGROUND: Non-neuronal cholinergic system (NNCS) contributes to various inflammatory airway diseases. However, the role of NNCS in severe asthma (SA) remains largely unexplored. OBJECTIVE: To explore airway NNCS in SA. METHODS: In this prospective cohort study based on the Australasian Severe Asthma Network in a real-world setting, patients with SA (n = 52) and non-SA (n = 104) underwent clinical assessment and sputum induction. The messenger RNA (mRNA) levels of NNCS components and proinflammatory cytokines in the sputum were detected using real-time quantitative polymerase chain reaction, and the concentrations of acetylcholine (Ach)-related metabolites were evaluated using liquid chromatography coupled with tandem mass spectrometry. Asthma exacerbations were prospectively investigated during the next 12 months. The association between NNCS and future asthma exacerbations was also analyzed. RESULTS: Patients with SA were less controlled and had worse airway obstruction, a lower bronchodilator response, higher doses of inhaled corticosteroids, and more add-on treatments. The sputum mRNA levels of NNCS components, such as muscarinic receptors M1R-M5R, OCT3, VACHT, and ACHE; proinflammatory cytokines; and Ach concentration in the SA group were significantly higher than those in the non-SA group. Furthermore, most NNCS components positively correlated with non-type (T) 2 inflammatory profiles, such as sputum neutrophils, IL8, and IL1B. In addition, the mRNA levels of sputum M2R, M3R, M4R, M5R, and VACHT were independently associated with an increased risk of moderate-to-severe asthma exacerbations. CONCLUSION: This study indicated that the NNCS was significantly activated in SA, leading to elevated Ach and was associated with clinical features, non-T2 inflammation, and future exacerbations of asthma, highlighting the potential role of the NNCS in the pathogenesis of SA. CLINICAL TRIAL REGISTRATION: ChiCTR-OOC-16009529 (http://www.chictr.org.cn).
Published: 2024

26. This title is unavailable for guests, please login to see more information.

Author: Aad, G, Aad, G, Abbott, B, Abbott, DC, Abeling, K, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Hoffman, AC Abusleme, Acharya, BS, Achkar, B, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Adelman, J, Adiguzel, A, Adorni, S, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Aguilar-Saavedra, JA, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Khoury, K Al, Alberghi, GL, Albert, J, Albicocco, P, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Alhroob, M, Ali, B, Ali, S, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Camelia, E Alunno, Estevez, M Alvarez, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Santos, SP Amor Dos, Amoroso, S, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, Pozo, JA Aparisi, Aparo, MA, Bella, L Aperio, Appelt, C, Aranzabal, N, Ferraz, V Araujo, Arcangeletti, C, Arce, ATH, Arena, E, Aad, G, Aad, G, Abbott, B, Abbott, DC, Abeling, K, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Hoffman, AC Abusleme, Acharya, BS, Achkar, B, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Adelman, J, Adiguzel, A, Adorni, S, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Aguilar-Saavedra, JA, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Khoury, K Al, Alberghi, GL, Albert, J, Albicocco, P, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Alhroob, M, Ali, B, Ali, S, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Camelia, E Alunno, Estevez, M Alvarez, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Santos, SP Amor Dos, Amoroso, S, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, Pozo, JA Aparisi, Aparo, MA, Bella, L Aperio, Appelt, C, Aranzabal, N, Ferraz, V Araujo, Arcangeletti, C, Arce, ATH, and Arena, E
Published: 2024

27. Accuracy versus precision in boosted top tagging with the ATLAS detector

Author: Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Bourdarios, C Adam, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Tamlihat, M Ait, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Estevez, M Alvarez, Fernandez, A Alvarez, Cardoso, M Alves, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amini, B, Amirie, KJ, Dos Santos, SP Amor, Amos, KR, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Antipov, E, Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Bourdarios, C Adam, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Tamlihat, M Ait, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Estevez, M Alvarez, Fernandez, A Alvarez, Cardoso, M Alves, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amini, B, Amirie, KJ, Dos Santos, SP Amor, Amos, KR, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, and Antipov, E
Abstract: The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.
Published: 2024

28. Probing the scalar WIMP-pion coupling with the first LUX-ZEPLIN data

Author: Zweig, EA, Zweig, EA, Yeh, M, Xu, J, Xiang, X, Xia, Q, Wright, CJ, Woodward, D, Woodford, S, Wolfs, FLH, Wisniewski, WJ, Williams, M, Whitis, TJ, Weeldreyer, L, Webb, RC, Watson, JR, Wang, Y, Wang, JJ, Wang, A, Velan, V, Valentino, O, Vaitkus, AC, Vacheret, A, Tronstad, DR, Tripathi, M, Trask, M, Tranter, J, Tovey, DR, Tong, Z, Timalsina, M, Tiedt, DR, Taylor, WC, Szydagis, M, Sumner, TJ, Suerfu, B, Stifter, K, Stevens, A, Stancu, I, Soria, J, Sorensen, P, Solovov, VN, Smith, R, Siniscalco, J, Sinev, G, Silva, C, Silk, JJ, Shutt, T, Shaw, S, Schnee, RW, Sazzad, ABMR, Santone, D, Rynders, D, Rushton, T, Rosero, R, Riyat, HS, Rischbieter, GRC, Riffard, Q, Rhyne, CA, Reichenbacher, J, Qie, Y, Piepke, A, Pershing, T, Perry, E, Pereira, G, Penning, B, Patton, SJ, Parveen, N, Pannifer, NJ, Palmer, J, Palladino, KJ, Orpwood, J, Oliver-Mallory, KC, Olcina, I, Nikoleyczik, JA, Nguyen, A, Neves, F, Nelson, HN, Naylor, A, Murphy, ASJ, Murdy, M, Mount, BJ, Morrison, E, Morales Mendoza, JD, Monzani, ME, Monte, A, Mizrachi, E, Miller, EH, McMonigle, R, McLaughlin, JB, McLaughlin, J, McKinsey, DN, McDowell, G, McCarthy, ME, Maupin, C, Mannino, RL, Manalaysay, A, Majewski, PA, Luitz, S, Lu, C, Lorenzon, W, Lopes, MI, Zweig, EA, Zweig, EA, Yeh, M, Xu, J, Xiang, X, Xia, Q, Wright, CJ, Woodward, D, Woodford, S, Wolfs, FLH, Wisniewski, WJ, Williams, M, Whitis, TJ, Weeldreyer, L, Webb, RC, Watson, JR, Wang, Y, Wang, JJ, Wang, A, Velan, V, Valentino, O, Vaitkus, AC, Vacheret, A, Tronstad, DR, Tripathi, M, Trask, M, Tranter, J, Tovey, DR, Tong, Z, Timalsina, M, Tiedt, DR, Taylor, WC, Szydagis, M, Sumner, TJ, Suerfu, B, Stifter, K, Stevens, A, Stancu, I, Soria, J, Sorensen, P, Solovov, VN, Smith, R, Siniscalco, J, Sinev, G, Silva, C, Silk, JJ, Shutt, T, Shaw, S, Schnee, RW, Sazzad, ABMR, Santone, D, Rynders, D, Rushton, T, Rosero, R, Riyat, HS, Rischbieter, GRC, Riffard, Q, Rhyne, CA, Reichenbacher, J, Qie, Y, Piepke, A, Pershing, T, Perry, E, Pereira, G, Penning, B, Patton, SJ, Parveen, N, Pannifer, NJ, Palmer, J, Palladino, KJ, Orpwood, J, Oliver-Mallory, KC, Olcina, I, Nikoleyczik, JA, Nguyen, A, Neves, F, Nelson, HN, Naylor, A, Murphy, ASJ, Murdy, M, Mount, BJ, Morrison, E, Morales Mendoza, JD, Monzani, ME, Monte, A, Mizrachi, E, Miller, EH, McMonigle, R, McLaughlin, JB, McLaughlin, J, McKinsey, DN, McDowell, G, McCarthy, ME, Maupin, C, Mannino, RL, Manalaysay, A, Majewski, PA, Luitz, S, Lu, C, Lorenzon, W, and Lopes, MI
Abstract: Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons. This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed. Using data from the first science run of the LUX-ZEPLIN dark matter experiment, containing 60 live days of data in a 5.5 tonne fiducial mass of liquid xenon, we report the results on a search for WIMP-pion interactions. We observe no significant excess and set an upper limit of 1.5 × 10−46 cm2 at a 90% confidence level for a WIMP mass of 33 GeV/c2 for this interaction.
Published: 2024

29. LNK/SH2B3 as a novel driver in juvenile myelomonocytic leukemia

Author: Wintering, Astrid, Wintering, Astrid, Hecht, Anna, Meyer, Julia, Wong, Eric B, Hübner, Juwita, Abelson, Sydney, Feldman, Kira, Kennedy, Vanessa E, Peretz, Cheryl AC, French, Deborah L, Maguire, Jean Ann, Jobaliya, Chintan, Vasquez, Marta Rojas, Desai, Sunil, Dulman, Robin, Nemecek, Eneida, Haines, Hilary, Hammad, Mahmoud, El Haddad, Alaa, Kogan, Scott C, Abdullaev, Zied, Chehab, Farid F, Tasian, Sarah K, Smith, Catherine C, Loh, Mignon L, Stieglitz, Elliot, Wintering, Astrid, Wintering, Astrid, Hecht, Anna, Meyer, Julia, Wong, Eric B, Hübner, Juwita, Abelson, Sydney, Feldman, Kira, Kennedy, Vanessa E, Peretz, Cheryl AC, French, Deborah L, Maguire, Jean Ann, Jobaliya, Chintan, Vasquez, Marta Rojas, Desai, Sunil, Dulman, Robin, Nemecek, Eneida, Haines, Hilary, Hammad, Mahmoud, El Haddad, Alaa, Kogan, Scott C, Abdullaev, Zied, Chehab, Farid F, Tasian, Sarah K, Smith, Catherine C, Loh, Mignon L, and Stieglitz, Elliot
Abstract: Mutations in five canonical Ras pathway genes (NF1, NRAS, KRAS, PTPN11 and CBL) are detected in nearly 90% of patients with juvenile myelomonocytic leukemia (JMML), a frequently fatal malignant neoplasm of early childhood. In this report, we describe seven patients diagnosed with SH2B3-mutated JMML, including five patients who were found to have initiating, loss-of-function mutations in the gene. SH2B3 encodes the adaptor protein LNK, a negative regulator of normal hematopoiesis upstream of the Ras pathway. These mutations were identified to be germline, somatic or a combination of both. Loss of function of LNK, which has been observed in other myeloid malignancies, results in abnormal proliferation of hematopoietic cells due to cytokine hypersensitivity and activation of the JAK/STAT signaling pathway. In vitro studies of induced pluripotent stem cell-derived JMML-like hematopoietic progenitor cells also demonstrated sensitivity of SH2B3-mutated hematopoietic progenitor cells to JAK inhibition. Lastly, we describe two patients with JMML and SH2B3 mutations who were treated with the JAK1/2 inhibitor ruxolitinib. This report expands the spectrum of initiating mutations in JMML and raises the possibility of targeting the JAK/STAT pathway in patients with SH2B3 mutations.
Published: 2024

30. Surveillance van legionellose in Nederland. Overzicht van clusters, bronnen en omgevingsfactoren tussen 2013-2022

Author: Reukers, DFM, Bartels, AA, Mulder, AC, Berry, DSF, Euser, S, Laarman, C, van den Berg, H, van Gageldonk-Lafeber, AB, Brandsema, PS, Reukers, DFM, Bartels, AA, Mulder, AC, Berry, DSF, Euser, S, Laarman, C, van den Berg, H, van Gageldonk-Lafeber, AB, and Brandsema, PS
Abstract: RIVM rapport:Als mensen met legionellabacteriën besmet raken, kunnen ze daar soms een longontsteking van krijgen. Sinds 2013 is het aantal meldingen van longontstekingen, bij mensen die in Nederland zijn besmet, meer dan verdubbeld: van 180 meldingen in 2013 naar 484 in 2022. In 2021 was er zelfs een piek van 555 meldingen. Mensen kunnen met legionellabacteriën besmet raken als zij deze bacterie inademen via hele kleine waterdruppeltjes. Een belangrijke verklaring van de stijging lijken de weersomstandigheden te zijn. Er zijn namelijk meer meldingen geweest in de jaren met warmere en nattere zomers. Tijdens vochtige, bewolkte weersomstandigheden kunnen legionellabacteriën namelijk langer overleven in de lucht en zich daardoor verder verspreiden. De laatste jaren komt de ziekte ook in de winter vaker voor dan tien jaar geleden. Het is waarschijnlijk dat dit ook in de winter met weersomstandigheden te maken heeft. Dit blijkt uit onderzoek van het RIVM. Mensen onder de 40 jaar worden zelden ziek van legionellabacteriën. Sommige groepen mensen hebben juist een grotere kans om een ernstige longontsteking te krijgen. Deze risicogroepen zijn ouderen, mensen met aandoeningen aan de luchtwegen, zoals COPD, mensen met een lagere afweer en rokers. Een deel van de stijging van het aantal meldingen is te verklaren omdat er meer ouderen zijn. Er zijn verschillende typen van de legionellabacterie. De meeste mensen worden ziek door Legionella pneumophila. Het onderzoek laat zien dat patiënten tussen 2013 en 2022 vooral besmet zijn via bronnen die water vernevelen in de buitenlucht. Denk aan afvalwaterzuiveringsinstallaties en 'natte koeltorens' (waterinstallaties die nodig zijn voor de airconditioning in vooral grote gebouwen, zoals kantoortorens en ziekenhuizen). Meer onderzoek is nodig om helder te krijgen hoe groot de invloed is van bronnen in de buitenlucht op de gestegen meldingen. En of ook andere bronnen hier invloed op hebben. Het RIVM adviseert beleidsmakers om risicogroepen via voorli, When people become infected with Legionella bacteria, they can sometimes develop pneumonia. Since 2013, the number of reports of pneumonia caused by Legionella in the Netherlands has more than doubled: from 180 cases in 2013 to 484 in 2022. In 2021, there was even a peak of 555 reported cases. People can become infected with Legionella bacteria if they inhale this bacteria via very small water droplets. An important explanation for this increase seems to be the weather conditions. More reports are made during years with warmer and wetter summers. During humid, cloudy weather conditions, Legionella bacteria can survive longer in the air and therefore spread further. However, in recent years more reports are made in the winter as well compared to 10 years ago. It is likely that weather conditions also play a role in winter. This is evident from an overview by RIVM. People under the age of 40 rarely become ill from Legionella bacteria. Some groups of people are more likely to develop severe pneumonia. These risk groups are the elderly, people with respiratory diseases such as COPD, people with a weakened immune system and smokers. Part of the increase in the number of reports can be explained by the fact that there are more elderly people. There are different types of Legionella bacteria. Most people become ill from Legionella pneumophila. This overview shows that people are mainly infected via sources that emit water droplets into the open air, such as wastewater treatment plants and 'wet cooling towers' (water installations that are needed for air conditioning in large buildings, such as office towers and hospitals). More research is needed to explain the influence of environmental sources on the increase in the number of reports and to find out whether there are other sources that contribute. RIVM advises policymakers to increase awareness among risk groups about Legionella infections. For example, increase awareness on the importance of setting hot water heaters or
Published: 2024

31. Tuberculose in Nederland 2023

Author: Slump, E, Anthony, R, Mulder, AC, Kamst-van Agterveld, MP, ter Linde, G, Schimmel, H, Stempher, HJ, Vrublenskaya, N, Slump, E, Anthony, R, Mulder, AC, Kamst-van Agterveld, MP, ter Linde, G, Schimmel, H, Stempher, HJ, and Vrublenskaya, N
Abstract: RIVM rapport:In 2023 is in Nederland bij 710 mensen de ziekte tuberculose (tbc(Tuberculose)) vastgesteld. Dit is 10 procent meer dan in de jaren 2020 tot en met 2022 tijdens de coronapandemie (gemiddeld 643 patiënten), maar 9 procent lager dan in de jaren voor de pandemie (gemiddeld 777 patiënten). Al tientallen jaren daalt het aantal tbc-patiënten in Nederland, het laagste aantal is tijdens de coronapandemie bereikt. Na de pandemie zijn de coronamaatregelen, zoals afstand houden en contacten tussen personen beperken, afgebouwd en is de tbc-bacterie weer vaker aan mensen overgedragen. Na het einde van de reisbeperkingen nam het aantal immigranten en asielzoekers in Nederland weer toe, ook uit landen waar tuberculose veel voorkomt. Zij worden na aankomst in Nederland verplicht gescreend op tuberculose en zo kan de ziekte snel worden opgespoord en behandeld. Tuberculose in Nederland komt vaker voor bij personen die niet in Nederland zijn geboren; in 2023 was dat bij 4 van de 5 zieken het geval. De meesten kwamen uit Eritrea (90), gevolgd door Somalië (60) en Marokko (37). In Afrika en Azië komt tuberculose veel voor. De infectieziekte tuberculose wordt veroorzaakt door een bacterie en kan besmettelijk zijn. Van de 710 tbc-patiënten in 2023 had 66 procent tuberculose in de longen, de overige patiënten hadden tuberculose buiten de longen. Van alle patiënten had 30 procent de besmettelijkste vorm (open tuberculose). Als een persoon wel besmet is met de bacterie maar (nog) geen tuberculose heeft, dan wordt dat een tuberculose-infectie genoemd. Door een tuberculose-infectie vroeg op te sporen kunnen mensen worden behandeld voordat ze ziek worden. Dit zorgt ervoor dat minder mensen tuberculose krijgen. In 2023 zijn er, naast de 710 personen die ziek waren, meer dan 1400 personen met een tuberculose-infectie gemeld. Ruim 40 procent is opgespoord door immigranten en asielzoekers uit landen waar tuberculose veel voorkomt, te testen. Bijna 30 procent is gevonden door bron- en contactonderzo, In 2023, 710 people in the Netherlands were diagnosed with tuberculosis (TB). This was a 10 percent increase on the number of diagnoses during the COVID-19 pandemic period from 2020 until 2022 (on average 643 patients), but a 9 percent decrease compared to the years before the pandemic (on average 777 patients). The number of TB patients in the Netherlands has been falling for decades, bottoming out during the COVID-19 pandemic. After the pandemic, the coronavirus measures – such as maintaining distance and limiting contact with other people – were eased and the TB bacteria was once again transmitted to other people more often. Following the end of travel restrictions, the number of immigrants and asylum seekers in the Netherlands – including from countries where TB is common – increased as well. Upon arrival in the Netherlands, these people undergo a mandatory screening for TB, so that the disease can be detected and treated quickly. In the Netherlands, TB is more prevalent among those not born in the country. In 2023, this was the case for four out of every five patients. Most patients were born in Eritrea (90), followed by Somalia (60) and Morocco (37). TB is widespread in Africa and Asia. TB is an infectious and potentially contagious disease caused by a bacterium. Of the 710 patients TB in 2023, 66 percent had pulmonary TB and the remaining patients had extrapulmonary TB. 30 percent of all patients had the most contagious type (open TB). People who have become infected with the bacterium but have not developed active TB yet are said to have contracted a TB infection. Early detection of TB infections makes it possible to treat people before they become ill. As a consequence, fewer people become ill with TB. In addition to the 710 people who became ill in 2023, more than 1,400 people were reported to have contracted a TB infection. More than 40 percent of infections was traced by screening immigrants and asylum seekers from countries where TB is common. Almost 30
Published: 2024

32. RSV-vaccinatie in ouderen. Achtergrondinformatie voor de Gezondheidsraad

Author: Knol, MJ, Teirlinck, AC, van Boven, M, van Gageldonk-Lafeber, AB, de Melker, HE, Knol, MJ, Teirlinck, AC, van Boven, M, van Gageldonk-Lafeber, AB, and de Melker, HE
Abstract: RIVM rapport:Respiratory syncytial virus (RSV) is a virus that causes respiratory infections. An RSV infection usually results in mild symptoms, but it can also be more severe, requiring hospitalisation. RSV is common among young children, particularly in autumn and winter, and can cause them to become seriously ill. It can also affect older adults, sometimes leading to hospitalisation and even death. The European Medicines Agency (EMA) has approved three vaccines for adults aged 60 and over to prevent illness caused by RSV. The Ministry of Health, Welfare and Sport (VWS) has asked the Health Council for advice on RSV vaccination for the elderly. To support this advice, the National Institute for Public Health and the Environment (RIVM) has gathered information for the Health Council. This information mainly concerns the estimated number of elderly people with RSV in the Netherlands and how severe their resulting symptoms are (disease burden). For various reasons, this is difficult to estimate. Firstly, the cause of a respiratory infection is not always investigated. This laboratory confirmation is usually not necessary because most infections resolve without treatment. Secondly, the laboratory test to detect RSV does not always give accurate results. Especially in older people, it is therefore not possible to detect all infections. Thirdly, hospitals do not always record a confirmed RSV infection in their data (coding). Using this limited available information, RIVM has estimated how many people are hospitalised each year due to an RSV infection by conducting an attribution analysis. It was estimated that, in the Netherlands, approximately 3,000 people aged 65 or older are hospitalised for RSV each year. This is about 1 in 1,000 people aged 65 and over. The likelihood of being hospitalised due to RSV increases with age. These results are in line with other (inter)national data., Het respiratoir syncytieel virus (RSV(Respiratoir Syncytieel Virus)) is een virus dat infecties aan de luchtwegen veroorzaakt. RSV komt in de herfst en winter veel voor bij jonge kinderen. Een RSV-infectie geeft meestal milde klachten, maar kan ook ernstiger verlopen waardoor kinderen in het ziekenhuis moeten worden opgenomen. Maar ook ouderen kunnen ziek worden van RSV. Zij kunnen hierdoor in het ziekenhuis terechtkomen en er ook aan overlijden. Het Europees Medicijnagentschap (EMA(European Medicines Agency)) heeft drie vaccins goedgekeurd voor volwassenen vanaf 60 jaar om ziekte door RSV te voorkomen. Het ministerie van VWS(Ministerie van Volksgezondheid, Welzijn en Sport) heeft de Gezondheidsraad gevraagd om een advies te geven over RSV-vaccinatie bij ouderen. Als ondersteuning voor dit advies heeft het RIVM informatie verzameld voor de Gezondheidsraad. Deze informatie gaat vooral over het geschatte aantal ouderen met RSV in Nederland en hoe ernstig ziek ze daarvan worden (ziektelast). Om verschillende redenen blijkt dat moeilijk te schatten. Ten eerste wordt bij een luchtweginfectie meestal niet onderzocht wat de oorzaak van de infectie is. Dat is ook niet nodig omdat de meeste infecties vanzelf, dus zonder behandeling, overgaan. Ten tweede geeft de laboratoriumtest om RSV aan te tonen niet altijd de goede uitslag. Daardoor worden vooral bij oudere mensen niet alle infecties aangetoond. Ten derde verwerken ziekenhuizen een aangetoonde RSV-infectie niet altijd in hun gegevens (coderingen). Het RIVM heeft met deze beperkt beschikbare informatie geschat hoeveel mensen per jaar vanwege een RSV-infectie worden opgenomen in het ziekenhuis. Een voorzichtige schatting is dat in Nederland elk jaar ongeveer 3000 mensen van 65 jaar of ouder voor RSV worden opgenomen. Dit is ongeveer 1 op de 1000 65-plussers. De kans om door RSV in het ziekenhuis te worden opgenomen is groter naarmate mensen ouder zijn. In de (inter)nationale wetenschappelijke literatuur zijn dezelfde verge
Published: 2024

33. Jaarrapportage monitor Gecombineerde leefstijl interventie (GLI) 2024

Author: Oosterhoff, M, de Weerdt, AC, Klein, PPF, Feenstra, T, de Wit, A, Oosterhoff, M, de Weerdt, AC, Klein, PPF, Feenstra, T, and de Wit, A
Abstract: RIVM rapport:Een Gecombineerde Leefstijlinterventie (GLI) is een behandeling voor mensen met overgewicht en obesitas. Het doel is om via een gezondere leefstijl een gezonder gewicht te bereiken. Dit gebeurt door aandacht te besteden aan onder andere voeding, beweging, slaap en stress. Deelnemers werken hier twee jaar aan. Sinds 2019 volgt het RIVM de ontwikkelingen rondom de GLI en de resultaten bij de deelnemers. Dit is de derde jaarrapportage, met cijfers tot 1 juni 2024. Sinds 2019 zijn 121.000 Nederlanders begonnen met de GLI. Bij de analyse van de cijfers wordt vooral gekeken naar het effect op gewicht, buikomvang en kwaliteit van leven. Aan het einde van het GLI-traject hebben deelnemers gemiddeld 5 procent gewicht verloren en is de buikomvang gemiddeld met bijna 5 procent afgenomen. De kwaliteit van leven is flink verbeterd: deze is 13 punten hoger dan bij het begin van de GLI, op een schaal van 0 (meest ongezond) tot 100 (meest gezond). De kwaliteit van leven is hoger bij deelnemers die meer dan 5 procent gewicht verliezen dan bij deelnemers die minder gewicht verliezen (15 punten hoger versus 11 punten hoger dan bij de start). Het RIVM heeft voor het eerst ook gekeken naar het effect van medicijnen met een gewichtsverlagende werking die tijdens de GLI worden gebruikt. Het kan gaan om medicijnen voor diabetes, waardoor mensen ook gewicht verliezen, maar soms ook om medicijnen die specifiek bedoeld zijn om af te vallen. Ongeveer een op de acht deelnemers (12 procent) gebruikt medicijnen met een gewichtsverlagende werking, de meesten omdat ze diabetes hebben. Slechts 1 procent van de GLI-deelnemers gebruikt medicijnen die specifiek bedoeld zijn om af te vallen. Dat zijn er te weinig om conclusies te kunnen trekken over effecten van déze obesitasmedicijnen bij GLI-deelnemers. Wel hebben we gekeken of de gemiddelde resultaten van de GLI worden vertekend doordat sommige deelnemers medicijnen met gewichtsverlagende werking gebruiken. De deelnemers zonder deze medicijnen vielen
Published: 2024

34. Combination of Searches for Higgs Boson Pair Production in pp Collisions at s=13 TeV with the ATLAS Detector

Author: Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Bourdarios, C Adam, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Tamlihat, M Ait, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Estevez, M Alvarez, Fernandez, A Alvarez, Cardoso, M Alves, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amini, B, Amirie, KJ, Dos Santos, SP Amor, Amos, KR, Amperiadou, D, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Bourdarios, C Adam, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Tamlihat, M Ait, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Estevez, M Alvarez, Fernandez, A Alvarez, Cardoso, M Alves, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amini, B, Amirie, KJ, Dos Santos, SP Amor, Amos, KR, Amperiadou, D, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, and Antel, C
Published: 2024

35. This title is unavailable for guests, please login to see more information.

Author: Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Adam Bourdarios, C, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Ait Tamlihat, M, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Alvarez Estevez, M, Alvarez Fernandez, A, Alves Cardoso, M, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amini, B, Amirie, KJ, Amor Dos Santos, SP, Amos, KR, Amperiadou, D, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Adam Bourdarios, C, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Ait Tamlihat, M, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Alvarez Estevez, M, Alvarez Fernandez, A, Alves Cardoso, M, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amini, B, Amirie, KJ, Amor Dos Santos, SP, Amos, KR, Amperiadou, D, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, and Antel, C
Published: 2024

36. The efficacy of acoustic indices for monitoring abundance and diversity in soil soundscapes

Author: Metcalf, OC, Nunes, CA, Abrahams, C, Baccaro, FB, Bradfer-Lawrence, T, Lees, AC, Vale, EM, Barlow, J, Metcalf, OC, Nunes, CA, Abrahams, C, Baccaro, FB, Bradfer-Lawrence, T, Lees, AC, Vale, EM, and Barlow, J
Abstract: Soil ecoacoustics is a rapidly emerging field heralded as a non-invasive method for monitoring soil fauna. Ecoacoustic analysis commonly uses acoustic indices to analyse soundscapes, linking them to ‘traditional’ biodiversity value metrics such as species richness and abundance, but it is not clear if this approach is appropriate for soil soundscapes. Furthermore, there are very few controlled experiments assessing how commonly used acoustic indices respond to different sound types, and none belowground. We address this by synthesising soil soundscapes with differing levels of acoustic richness, abundance, and evenness using soil recordings from the UK, France, and Brazil. Applying 14 acoustic indices on 1-minute soundscapes, we assessed: 1) how changes in acoustic diversity impact acoustic indices and 2) how accurately combinations of indices predict biodiversity metrics. Finally we assessed 3) whether gamma acoustic richness can be predicted accurately using multiple acoustic index scores from repeated surveys, whilst experimentally altering the alpha and beta diversity components. We find that acoustic abundance strongly affects values of acoustic indices designed to quantify the number of sound events in a soundscape, and that a combination of these indices can accurately predict abundance at 1-minute timescales. Combinations of indices could predict acoustic richness when richness values were low, but were ineffective for evenness. Additionally, acoustic indices were poor predictors of gamma diversity, especially when gamma was driven solely by beta diversity. Overall, we found that acoustic indices were good predictors of acoustic abundance, but should be used with caution for other diversity metrics.
Published: 2024

37. Sensor response and radiation damage effects for 3D pixels in the ATLAS IBL Detector

Author: Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Adam Bourdarios, C, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Ait Tamlihat, M, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Alvarez Estevez, M, Alvarez Fernandez, A, Alves Cardoso, M, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amini, B, Amirie, KJ, Amor Dos Santos, SP, Amos, KR, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Antipov, E, Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Adam Bourdarios, C, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Ait Tamlihat, M, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Alvarez Estevez, M, Alvarez Fernandez, A, Alves Cardoso, M, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amini, B, Amirie, KJ, Amor Dos Santos, SP, Amos, KR, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, and Antipov, E
Abstract: Pixel sensors in 3D technology equip the outer ends of the staves of the Insertable B Layer (IBL), the innermost layer of the ATLAS Pixel Detector, which was installed before the start of LHC Run 2 in 2015. 3D pixel sensors are expected to exhibit more tolerance to radiation damage and are the technology of choice for the innermost layer in the ATLAS tracker upgrade for the HL-LHC programme. While the LHC has delivered an integrated luminosity of ≃ 235 fb-1 since the start of Run 2, the 3D sensors have received a non-ionising energy deposition corresponding to a fluence of ≃ 8.5 × 1014 1 MeV neutron-equivalent cm-2 averaged over the sensor area. This paper presents results of measurements of the 3D pixel sensors' response during Run 2 and the first two years of Run 3, with predictions of its evolution until the end of Run 3 in 2025. Data are compared with radiation damage simulations, based on detailed maps of the electric field in the Si substrate, at various fluence levels and bias voltage values. These results illustrate the potential of 3D technology for pixel applications in high-radiation environments.
Published: 2024

38. Search for pair-produced vectorlike quarks coupling to light quarks in the lepton plus jets final state using 13 TeV pp collisions with the ATLAS detector

Author: Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Bourdarios, C Adam, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Tamlihat, M Ait, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Estevez, M Alvarez, Fernandez, A Alvarez, Cardoso, M Alves, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amirie, KJ, Dos Santos, SP Amor, Amos, KR, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Antipov, E, Antonelli, M, Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Bourdarios, C Adam, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Tamlihat, M Ait, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Estevez, M Alvarez, Fernandez, A Alvarez, Cardoso, M Alves, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amirie, KJ, Dos Santos, SP Amor, Amos, KR, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Antipov, E, and Antonelli, M
Abstract: A search is presented for the pair production of heavy vectorlike quarks (VLQs) that each decay into a W boson and a light quark. This study focuses on events where one W boson decays into leptons and the other into hadrons. The search analyzed 140 fb−1 of pp collision data with s=13 TeV, recorded by the ATLAS detector from 2015 to 2018 during run 2 of the Large Hadron Collider. The final state is characterized by a high-transverse-momentum isolated electron or muon, large missing transverse momentum, multiple small-radius jets, and a single large-radius jet identified as originating from the hadronic decay of a boosted W boson. With higher center-of-mass energy and integrated luminosity than in the run 1 search, and improved analysis tools, this analysis excludes VLQs (Q) with masses below 1530 GeV at 95% confidence level for the branching ratio B(Q→Wq)=1, an improvement of 840 GeV on the previous ATLAS limit. © 2024 CERN, for the ATLAS Collaboration 2024 CERN
Published: 2024

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Author: Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Hoffman, AC Abusleme, Acharya, BS, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Tamlihat, M Ait, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Estevez, M Alvarez, Fernandez, A Alvarez, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Dos Santos, SP Amor, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, Pozo, JA Aparisi, Aparo, MA, Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Hoffman, AC Abusleme, Acharya, BS, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Tamlihat, M Ait, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Estevez, M Alvarez, Fernandez, A Alvarez, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Dos Santos, SP Amor, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, Pozo, JA Aparisi, and Aparo, MA
Published: 2024

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Author: Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Hoffman, AC Abusleme, Acharya, BS, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Tamlihat, M Ait, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Estevez, M Alvarez, Fernandez, A Alvarez, Cardoso, M Alves, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Dos Santos, SP Amor, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, Pozo, JA Aparisi, Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Hoffman, AC Abusleme, Acharya, BS, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Tamlihat, M Ait, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Estevez, M Alvarez, Fernandez, A Alvarez, Cardoso, M Alves, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Dos Santos, SP Amor, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, and Pozo, JA Aparisi
Published: 2024

41. Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at s=13 TeV with the ATLAS Detector

Author: Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Hoffman, AC Abusleme, Acharya, BS, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Tamlihat, M Ait, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Estevez, M Alvarez, Fernandez, A Alvarez, Cardoso, M Alves, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Dos Santos, SP Amor, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Anulli, F, Aoki, M, Aoki, T, Pozo, JA Aparisi, Aparo, MA, Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Hoffman, AC Abusleme, Acharya, BS, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Tamlihat, M Ait, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Flores, CA Allendes, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Estevez, M Alvarez, Fernandez, A Alvarez, Cardoso, M Alves, Alviggi, MG, Aly, M, Coutinho, Y Amaral, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Dos Santos, SP Amor, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Anulli, F, Aoki, M, Aoki, T, Pozo, JA Aparisi, and Aparo, MA
Published: 2024

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Author: Aad, G, Aad, G, Abbott, B, Abbott, DC, Abeling, K, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Abusleme Hoffman, AC, Acharya, BS, Achkar, B, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Adelman, J, Adiguzel, A, Adorni, S, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Aguilar-Saavedra, JA, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aizenberg, I, Akbiyik, M, Akesson, TPA, Akimov, AV, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Alhroob, M, Ali, B, Ali, S, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Camelia, E Alunno, Alvarez Estevez, M, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amor Dos Santos, SP, Amoroso, S, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, Aparisi Pozo, JA, Aparo, MA, Bella, L Aperio, Appelt, C, Aranzabal, N, Araujo Ferraz, V, Arcangeletti, C, Arce, ATH, Arena, E, Aad, G, Aad, G, Abbott, B, Abbott, DC, Abeling, K, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Abusleme Hoffman, AC, Acharya, BS, Achkar, B, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Adelman, J, Adiguzel, A, Adorni, S, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Aguilar-Saavedra, JA, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aizenberg, I, Akbiyik, M, Akesson, TPA, Akimov, AV, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Alhroob, M, Ali, B, Ali, S, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Camelia, E Alunno, Alvarez Estevez, M, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amor Dos Santos, SP, Amoroso, S, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, Aparisi Pozo, JA, Aparo, MA, Bella, L Aperio, Appelt, C, Aranzabal, N, Araujo Ferraz, V, Arcangeletti, C, Arce, ATH, and Arena, E
Published: 2024

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Author: Aad, G, Aad, G, Abbott, B, Abbott, DC, Abud, A Abed, Abeling, K, Abhayasinghe, DK, Abidi, SH, Abramowicz, H, Abreu, H, Abulaiti, Y, Hoffman, AC Abusleme, Acharya, BS, Achkar, B, Adam, L, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Adelman, J, Adiguzel, A, Adorni, S, Adye, T, Affolder, AA, Afik, Y, Agapopoulou, C, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Aguilar-Saavedra, JA, Ahmad, A, Ahmadov, F, Ahmed, WS, Ai, X, Aielli, G, Aizenberg, I, Akatsuka, S, Akbiyik, M, Åkesson, TPA, Akimov, AV, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Verzini, MJ Alconada, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Alhroob, M, Ali, B, Ali, S, Aliev, M, Alimonti, G, Allaire, C, Allbrooke, BMM, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Camelia, E Alunno, Estevez, M Alvarez, Alviggi, MG, Coutinho, Y Amaral, Ambler, A, Ambroz, L, Amelung, C, Amidei, D, Dos Santos, SP Amor, Amoroso, S, Amrouche, CS, Anastopoulos, C, Andari, N, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Pozo, JA Aparisi, Aparo, MA, Bella, L Aperio, Aranzabal, N, Ferraz, V Araujo, Arcangeletti, C, Arce, ATH, Arena, E, Arguin, J-F, Aad, G, Aad, G, Abbott, B, Abbott, DC, Abud, A Abed, Abeling, K, Abhayasinghe, DK, Abidi, SH, Abramowicz, H, Abreu, H, Abulaiti, Y, Hoffman, AC Abusleme, Acharya, BS, Achkar, B, Adam, L, Bourdarios, C Adam, Adamczyk, L, Adamek, L, Addepalli, SV, Adelman, J, Adiguzel, A, Adorni, S, Adye, T, Affolder, AA, Afik, Y, Agapopoulou, C, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Aguilar-Saavedra, JA, Ahmad, A, Ahmadov, F, Ahmed, WS, Ai, X, Aielli, G, Aizenberg, I, Akatsuka, S, Akbiyik, M, Åkesson, TPA, Akimov, AV, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Verzini, MJ Alconada, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Alhroob, M, Ali, B, Ali, S, Aliev, M, Alimonti, G, Allaire, C, Allbrooke, BMM, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Camelia, E Alunno, Estevez, M Alvarez, Alviggi, MG, Coutinho, Y Amaral, Ambler, A, Ambroz, L, Amelung, C, Amidei, D, Dos Santos, SP Amor, Amoroso, S, Amrouche, CS, Anastopoulos, C, Andari, N, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Pozo, JA Aparisi, Aparo, MA, Bella, L Aperio, Aranzabal, N, Ferraz, V Araujo, Arcangeletti, C, Arce, ATH, Arena, E, and Arguin, J-F
Abstract: A search for high-mass resonances decaying into a Formula Presented-lepton and a neutrino using proton-proton collisions at a center-of-mass energy of Formula Presented is presented. The full run 2 data sample corresponding to an integrated luminosity of Formula Presented recorded by the ATLAS experiment in the years 2015-2018 is analyzed. The Formula Presented-lepton is reconstructed in its hadronic decay modes and the total transverse momentum carried out by neutrinos is inferred from the reconstructed missing transverse momentum. The search for new physics is performed on the transverse mass between the Formula Presented-lepton and the missing transverse momentum. No excess of events above the Standard Model expectation is observed and upper exclusion limits are set on the Formula Presented production cross section. Heavy Formula Presented vector bosons with masses up to 5.0 TeV are excluded at 95% confidence level, assuming that they have the same couplings as the Standard Model Formula Presented boson. For nonuniversal couplings, Formula Presented bosons are excluded for masses less than 3.5-5.0 TeV, depending on the model parameters. In addition, model-independent limits on the visible cross section times branching ratio are determined as a function of the lower threshold on the transverse mass of the Formula Presented-lepton and missing transverse momentum.
Published: 2024

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Author: Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Adam Bourdarios, C, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Ait Tamlihat, M, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Alvarez Estevez, M, Alvarez Fernandez, A, Alves Cardoso, M, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amirie, KJ, Amor Dos Santos, SP, Amos, KR, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Antipov, E, Aad, G, Aad, G, Aakvaag, E, Abbott, B, Abdelhameed, S, Abeling, K, Abicht, NJ, Abidi, SH, Aboelela, M, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Ackermann, A, Adam Bourdarios, C, Adamczyk, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Ait Tamlihat, M, Aitbenchikh, B, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Aktas, S, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Alegria, ZL, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alsolami, ZMK, Alvarez Estevez, M, Alvarez Fernandez, A, Alves Cardoso, M, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amirie, KJ, Amor Dos Santos, SP, Amos, KR, An, S, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Anderson, AC, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, and Antipov, E
Published: 2024

45. Measurement and interpretation of same-sign W boson pair production in association with two jets in pp collisions at s = 13 TeV with the ATLAS detector

Author: Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Abusleme Hoffman, AC, Acharya, BS, Adam Bourdarios, C, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Ait Tamlihat, M, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alvarez Estevez, M, Alvarez Fernandez, A, Alves Cardoso, M, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amor Dos Santos, SP, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Anulli, F, Aoki, M, Aoki, T, Aparisi Pozo, JA, Aparo, MA, Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Abusleme Hoffman, AC, Acharya, BS, Adam Bourdarios, C, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Aikot, A, Ait Tamlihat, M, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alvarez Estevez, M, Alvarez Fernandez, A, Alves Cardoso, M, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amor Dos Santos, SP, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Anulli, F, Aoki, M, Aoki, T, Aparisi Pozo, JA, and Aparo, MA
Abstract: This paper presents the measurement of fiducial and differential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W±W±jj) using 139 fb−1 of proton-proton collision data recorded at a centre-of-mass energy of s = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity difference. The measured fiducial cross sections for electroweak and inclusive W±W±jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.) fb and 3.38 ± 0.22 (stat.) ± 0.19 (syst.) fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confidence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H±± mass near 450 GeV, with a global significance of 2.5 standard deviations.
Published: 2024

46. Test of CP-invariance of the Higgs boson in vector-boson fusion production and in its decay into four leptons

Author: Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Abusleme Hoffman, AC, Acharya, BS, Adam Bourdarios, C, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Ait Tamlihat, M, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alvarez Estevez, M, Alvarez Fernandez, A, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amor Dos Santos, SP, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, Aparisi Pozo, JA, Aparo, MA, Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Abusleme Hoffman, AC, Acharya, BS, Adam Bourdarios, C, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Ait Tamlihat, M, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alvarez Estevez, M, Alvarez Fernandez, A, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amor Dos Santos, SP, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, Aparisi Pozo, JA, and Aparo, MA
Published: 2024

47. Measurement of the total and differential cross-sections of tt¯W production in pp collisions at s = 13 TeV with the ATLAS detector

Author: Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Abusleme Hoffman, AC, Acharya, BS, Adam Bourdarios, C, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Ait Tamlihat, M, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alvarez Estevez, M, Alvarez Fernandez, A, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amor Dos Santos, SP, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, Aparisi Pozo, JA, Aparo, MA, Aad, G, Aad, G, Abbott, B, Abeling, K, Abicht, NJ, Abidi, SH, Aboulhorma, A, Abramowicz, H, Abreu, H, Abulaiti, Y, Abusleme Hoffman, AC, Acharya, BS, Adam Bourdarios, C, Adamczyk, L, Adamek, L, Addepalli, SV, Addison, MJ, Adelman, J, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agaras, MN, Agarwala, J, Aggarwal, A, Agheorghiesei, C, Ahmad, A, Ahmadov, F, Ahmed, WS, Ahuja, S, Ai, X, Aielli, G, Ait Tamlihat, M, Aitbenchikh, B, Aizenberg, I, Akbiyik, M, Åkesson, TPA, Akimov, AV, Akiyama, D, Akolkar, NN, Al Khoury, K, Alberghi, GL, Albert, J, Albicocco, P, Albouy, GL, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alfonsi, A, Alfonsi, F, Algren, M, Alhroob, M, Ali, B, Ali, HMJ, Ali, S, Alibocus, SW, Aliev, M, Alimonti, G, Alkakhi, W, Allaire, C, Allbrooke, BMM, Allen, JF, Allendes Flores, CA, Allport, PP, Aloisio, A, Alonso, F, Alpigiani, C, Alvarez Estevez, M, Alvarez Fernandez, A, Alviggi, MG, Aly, M, Amaral Coutinho, Y, Ambler, A, Amelung, C, Amerl, M, Ames, CG, Amidei, D, Amor Dos Santos, SP, Amos, KR, Ananiev, V, Anastopoulos, C, Andeen, T, Anders, JK, Andrean, SY, Andreazza, A, Angelidakis, S, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antipov, E, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aoki, T, Aparisi Pozo, JA, and Aparo, MA
Published: 2024

48. Updated insights of active cosmetic ingredients against blue light: In vivo and in vitro evidence

Author: Ferreira, L, Torres, B, Hameed, H, Vieira, ACF, Singh, SK, Dua, K, Veiga, F, Pires, PC, Mazzola, PG, Paiva-Santos, AC, Ferreira, L, Torres, B, Hameed, H, Vieira, ACF, Singh, SK, Dua, K, Veiga, F, Pires, PC, Mazzola, PG, and Paiva-Santos, AC
Abstract: The exponential increase in screen usage during the COVID-19 pandemic has raised concerns about higher exposure to blue light (BL) from electronic devices and raising concerns about its effects on skin health. BL significantly contributes to skin photoaging, which has aroused considerable interest among researchers due to its proximity in wavelength range to ultraviolet (UV) radiation. Owing to this high exposure and considering the high dynamism of the dermocosmetic market, formulations started to appear directed to combat skin photoaging, stimulating the interest of consumers with marketing strategies and appealing claims. These formulations have the purpose of preventing skin photoaging through the use of UV filters, providing broad UV and BL protection; and incorporation of compounds with mainly antioxidant and photoprotective properties, that allow the mitigation of various damaging effects that can occur as a result of the formation of free radicals, mainly DNA damage, hyperpigmentation, and deregulation of the circadian rhythm. These substances present limitations in solubility and photostability, i.e. high susceptibility to degradation and, consequently, a higher risk of toxicity. To circumvent these issues and maximize the antioxidant potential of these components, nanodelivery systems offer multifunctional and targeted approaches that can significantly enhance their bioavailability, efficacy, and safety. Overall, this review explores the beneficial and adverse effects of BL on the skin, with a focus on the most recent in vivo and in vitro studies of active ingredients, and the application of nanodelivery systems to enhance its performance. The databases used for literature research were Pubmed, Science Direct, and Web of Science, while research on major patent innovations was made through notorious patent databases, such as Patentscope and Espacenet, through the period of 2019–2024. Additionally, this review addresses the sustainability challenges in the d
Published: 2024

49. Forecasting the effects of smoking prevalence scenarios on years of life lost and life expectancy from 2022 to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Author: Bryazka, D, Reitsma, MB, Abate, YH, Abd Al Magied, AHA, Abdelkader, A, Abdollahi, A, Abdoun, M, Abdulkader, RS, Abeldaño Zuñiga, RA, Abhilash, ES, Abiodun, OO, Andrei, CL, Zhang, L, Zhong, CC, Zhou, SC, Zhu, B, Zielińska, M, Zoghi, G, Zyoud, SH, Vollset, SE, Gakidou, E, Andrei, T, Ansari, MT, Anuoluwa, IA, Anvari, S, Anwar, SL, Anyasodor, AE, Arabloo, J, Arafa, EA, Aravkin, AY, Abiodun, O, Areda, D, Aregawi, BB, Aremu, O, Artamonov, AA, Asgedom, AA, Asghari-Jafarabadi, M, Ashemo, MY, Ashraf, T, Astell-Burt, T, Athari, SS, Aboagye, RG, Atorkey, P, Atreya, A, Aujayeb, A, Awotidebe, AW, Ayano, G, Aychiluhm, SB, Azadnajafabad, S, Azzam, AY, Babu, GR, Bahrami Taghanaki, P, Abreu, LG, Bahramian, S, Bai, R, Bakkannavar, SM, Balakrishnan, S, Bam, K, Banach, M, Bandyopadhyay, S, Baran, MF, Barchitta, M, Bardhan, M, Abtahi, D, Barker-Collo, SL, Barrow, A, Bashiru, HA, Basiru, A, Bastan, M-M, Basu, S, Batra, K, Bayati, M, Behnoush, AH, Abualruz, H, Bell, SL, Belo, L, Beneke, AA, Bennett, DA, Bensenor, IM, Beran, A, Bermudez, ANC, Beyene, HB, Bhagat, DS, Bhagavathula, AS, Abubakar, B, Bhala, N, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bhat, AN, Bhattacharjee, NV, Bhattacharjee, P, Bhatti, JS, Bilgin, C, Biswas, A, Abu-Rmeileh, NME, Biswas, B, Boachie, MK, Bogale, EK, Bora Basara, B, Borhany, H, Bosoka, SA, Bouaoud, S, Boyko, EJ, Brenner, H, Brunoni, AR, Aburuz, S, Bugiardini, R, Bulamu, NB, Bustanji, Y, Butt, ZA, Caetano dos Santos, FL, Calina, D, Cao, C, Cao, F, Capodici, A, Cárdenas, R, Abu-Zaid, A, Carreras, G, Castaldelli-Maia, JM, Cattaruzza, MS, Caye, A, Cegolon, L, Cenko, E, Cerrai, S, Chakraborty, S, Chandika, RM, Chandrasekar, EK, Adane, MM, Chattu, VK, Chaudhary, AA, Chaurasia, A, Chen, A-T, Chen, G, Chen, H, Chen, MX, Chen, S, Cheng, KJG, Chi, G, Adebiyi, AO, Chichagi, F, Chimoriya, R, Chirinos-Caceres, JL, Chitheer, A, Chong, B, Chong, CL, Chong, YY, Chopra, H, Choudhari, SG, Chu, D-T, Adegboye, OA, Chukwu, IS, Chung, S-C, Chutiyami, M, Conde, J, Corlateanu, A, Criqui, MH, Cruz-Martins, N, da Silva, AG, Dadras, O, Dai, S, Adekanmbi, V, Dai, X, Damiani, G, Dandona, L, Dandona, R, Darcho, SD, Darvishi Cheshmeh Soltani, R, Das, S, Dash, NR, Davletov, K, Debele, AT, Adewuyi, HO, Debopadhaya, S, Demant, D, Desai, HD, Devegowda, D, Dewan, SMR, Dhali, A, Dhane, AS, Dhulipala, VR, Do, TC, Dodangeh, M, Adnani, QES, Doegah, PT, Dohare, S, Dongarwar, D, D'Oria, M, Doshi, OP, Doshi, RP, Dowou, RK, Dsouza, AC, Dsouza, HL, Dsouza, VS, Adzigbli, LA, Duncan, BB, Duraes, AR, Dziedzic, AM, E'mar, AR, Ebrahimi, A, Ebrahimi, N, Ebrahimi Kalan, M, Edvardsson, D, Edvardsson, K, Efendi, F, Afaghi, S, Effendi, DE, Eghbali, F, Ekholuenetale, M, El Arab, RA, El Bayoumy, IF, El Sayed, I, Elbarazi, I, Elhadi, M, El-Huneidi, W, Elmonem, MA, Afolabi, AA, ELNahas, G, Elsohaby, I, Eltaha, C, Eltahir, ME, Emamverdi, M, Emeto, TI, Erku, DA, Etaee, F, Ezenwankwo, EF, Fabin, N, Afzal, MS, Fagbamigbe, AF, Fagbule, OF, Faghani, S, Fahim, A, Fakhradiyev, IR, Falzone, L, Farooque, U, Fatehizadeh, A, Fatima, Z, Fauk, NK, Afzal, S, Fazylov, T, Feizkhah, A, Fekadu, G, Feng, X, Ferrara, P, Ferreira, N, Feyisa, BR, Filippidis, FT, Fischer, F, Flor, LS, Agodi, A, Foigt, NA, Fortuna Rodrigues, C, Foschi, M, G, S, Gaal, PA, Gadanya, MA, Gaidhane, AM, Gajdács, M, Gallus, S, Gandhi, AP, Agyemang-Duah, W, Ganesan, B, Gautam, P, Gautam, RK, Gebregergis, MW, Gebrehiwot, M, Gebremeskel, TG, Getacher, L, Ghadirian, F, Ghazy, RM, Gholamrezanezhad, A, Ahinkorah, BO, Ghorbani, M, Ghozy, S, Gil, AU, Gil, GF, Gnedovskaya, EV, Goel, S, Goharinezhad, S, Goldust, M, Golechha, M, Goleij, P, Ahlstrom, AJ, Golinelli, D, Gorini, G, Gouravani, M, Grada, A, Grivna, M, Grover, S, Guan, S-Y, Gubari, MIM, Guha, A, Guicciardi, S, Ahmad, A, Gulati, S, Gunawardane, DA, Gunturu, S, Guo, Z, Gupta, AK, Gupta, B, Gupta, I, Gupta, M, Gupta, R, Gupta, S, Ahmad, D, Gupta, VB, Gupta, V, Gupta, VK, Hadei, M, Hadi, NR, Hajj Ali, A, Halboub, ES, Hamdy, NM, Hamidi, S, Hammoud, A, Ahmad, MM, Hankey, GJ, Hargono, A, Haro, JM, Hasaballah, AI, Hasan, F, Hasan, MK, Hasnain, MS, Hassan, A, Hassan, II, Hassan, S, Ahmad, S, Hay, SI, Heibati, B, Heidari, M, Hemmati, M, Hendrie, D, Herteliu, C, Heyi, DZ, Hezam, K, Hiraike, Y, Hoan, NQ, Holla, R, Horita, N, Hossain, MM, Hossain, S, Hosseinzadeh, H, Hostiuc, M, Hostiuc, S, Huang, J, Humayun, A, Hussain, J, Ahmadi, A, Hwang, B-F, Ibitoye, SE, Ikeda, N, Ikiroma, A, Ilesanmi, OS, Ilic, IM, Ilic, MD, Immurana, M, Inbaraj, LR, Iqhrammullah, M, Ahmed, A, Irham, LM, Islam, MR, Islam, SMS, Islami, F, Isola, G, Itumalla, R, Iwagami, M, Iyer, M, J, V, Jaafari, J, Jacob, L, Jafarzadeh, A, Jaggi, K, Jahanmehr, N, Jain, A, Jain, N, Jairoun, AA, Jaka, S, Jakovljevic, M, Jalilzadeh Yengejeh, R, Ahmed, H, Jamshidi, E, Janodia, MD, Jawaid, T, Jayapal, SK, Jayaram, S, Jayasinghe, RD, Jebai, R, Jee, SH, Jeswani, BM, Jiang, H, Ahmed, MB, Jokar, M, Jonas, JB, Joo, T, Joseph, N, Joshua, CE, Jozwiak, JJ, Jürisson, M, K, V, Kabir, A, Kabir, Z, 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JA, Yin, D, Yon, DK, Yonemoto, N, Yoon, S-J, Yu, C, Yuan, C-W, Zakham, F, Zeariya, MGM, Zhang, H, and Zhang, J
Published: 2024

50. Introducing CRC SAAFE: a new Cooperative Research Centre (CRC) focused on managing AMR in agriculture and the environment

Author: Donner, E, Magalhães, RJS, Barnes, AC, Jex, A, Jarocki, V, Drigo, B, Djordjevic, S, Ashbolt, NJ, Donner, E, Magalhães, RJS, Barnes, AC, Jex, A, Jarocki, V, Drigo, B, Djordjevic, S, and Ashbolt, NJ
Abstract: Antimicrobial resistance (AMR) is a complex challenge that poses a critical threat to food and water safety and security as well as to human, animal and environmental health. It is projected to cost the global economy US$100 trillion by 2050. Australia’s new Cooperative Research Centre (CRC) for Solving Antimicrobial Resistance in Agribusiness, Food and Environments (SAAFE) is part of Australia’s One Health approach to mitigating AMR. SAAFE’s 10-year, A$150-million industry-led program will help protect Australia’s food and agribusiness industries, and the environments in which they operate, from the growing threat of AMR. Through its research programs, CRC SAAFE uses a partner-based approach to assist industries to monitor, analyse and mitigate AMR, with projects spanning horticulture, viticulture, aquaculture, animal industries, water and waste.
Published: 2024

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