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61 Network Segregation Predicts Processing Speed in the Cognitively Healthy Oldest-old
- Sara A Nolin, Mary E Faulkner, Paul Stewart, Leland Fleming, Stacy Merritt, Roxanne F Rezaei, Pradyumna K Bharadwaj, Mary Kathryn Franchetti, Daniel A Raichlen, Courtney J Jessup, Lloyd Edwards, G Alex Hishaw, Emily J Van Etten, Theodore P Trouard, David S Geldmacher, Virginia G Wadley, Noam Alperin, Eric C Porges, Adam J Woods, Ronald A Cohen, Bonnie E Levin, Tatjana Rundek, Gene E Alexander, Kristina M Visscher
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 367-368
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Objective:
Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.
Participants and Methods:Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.
Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.
Results:We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).
Conclusions:This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.
Review: The variability of the eating quality of beef can be reduced by predicting consumer satisfaction
- S. P. F. Bonny, J.-F. Hocquette, D. W. Pethick, I. Legrand, J. Wierzbicki, P. Allen, L. J. Farmer, R. J. Polkinghorne, G. E. Gardner
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The Meat Standards Australia (MSA) grading scheme has the ability to predict beef eating quality for each ‘cut×cooking method combination’ from animal and carcass traits such as sex, age, breed, marbling, hot carcass weight and fatness, ageing time, etc. Following MSA testing protocols, a total of 22 different muscles, cooked by four different cooking methods and to three different degrees of doneness, were tasted by over 19 000 consumers from Northern Ireland, Poland, Ireland, France and Australia. Consumers scored the sensory characteristics (tenderness, flavor liking, juiciness and overall liking) and then allocated samples to one of four quality grades: unsatisfactory, good-every-day, better-than-every-day and premium. We observed that 26% of the beef was unsatisfactory. As previously reported, 68% of samples were allocated to the correct quality grades using the MSA grading scheme. Furthermore, only 7% of the beef unsatisfactory to consumers was misclassified as acceptable. Overall, we concluded that an MSA-like grading scheme could be used to predict beef eating quality and hence underpin commercial brands or labels in a number of European countries, and possibly the whole of Europe. In addition, such an eating quality guarantee system may allow the implementation of an MSA genetic index to improve eating quality through genetics as well as through management. Finally, such an eating quality guarantee system is likely to generate economic benefits to be shared along the beef supply chain from farmers to retailors, as consumers are willing to pay more for a better quality product.
Willingness to pay for beef is highly transferrable between different consumer groups
- S. P. F. Bonny, J.-F. Hocquette, D. W. Pethick, I. Legrand, J. Wierzbicki, P. Allen, L. J. Farmer, R. J. Polkinghorne, G. E. Gardner
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- Journal:
- Advances in Animal Biosciences / Volume 8 / Issue s1 / October 2017
- Published online by Cambridge University Press:
- 03 October 2017, pp. s72-s75
- Print publication:
- October 2017
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Accurately quantifying a consumer’s willingness to pay (WTP) for beef of different eating qualities is intrinsically linked to the development of eating-quality-based meat grading systems, and therefore the delivery of consistent, quality beef to the consumer. Following Australian MSA (Meat Standards Australia) testing protocols, over 19 000 consumers from Northern Ireland, Poland, Ireland, France and Australia were asked to detail their willingness to pay for beef from one of four categories that best described the sample; unsatisfactory, good-every-day, better-than-every-day or premium quality. These figures were subsequently converted to a proportion relative to the good-every-day category (P-WTP) to allow comparison between different currencies and time periods. Consumers also answered a short demographic questionnaire. Consumer P-WTP was found to be remarkably consistent between different demographic groups. After quality grade, by far the greatest influence on P-WTP was country of origin. This difference was unable to be explained by the other demographic factors examined in this study, such as occupation, gender, frequency of consumption and the importance of beef in the diet. Therefore, we can conclude that the P-WTP for beef is highly transferrable between different consumer groups, but not countries.
Untrained consumer assessment of the eating quality of European beef: 2. Demographic factors have only minor effects on consumer scores and willingness to pay
- S. P. F. Bonny, G. E. Gardner, D. W. Pethick, P. Allen, I. Legrand, J. Wierzbicki, L. J. Farmer, R. J. Polkinghorne, J.-F. Hocquette
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The beef industry must become more responsive to the changing market place and consumer demands. An essential part of this is quantifying a consumer’s perception of the eating quality of beef and their willingness to pay for that quality, across a broad range of demographics. Over 19 000 consumers from Northern Ireland, Poland, Ireland and France each tasted seven beef samples and scored them for tenderness, juiciness, flavour liking and overall liking. These scores were weighted and combined to create a fifth score, termed the Meat Quality 4 score (MQ4) (0.3×tenderness, 0.1×juiciness, 0.3×flavour liking and 0.3×overall liking). They also allocated the beef samples into one of four quality grades that best described the sample; unsatisfactory, good-every-day, better-than-every-day or premium. After the completion of the tasting panel, consumers were then asked to detail, in their own currency, their willingness to pay for these four categories which was subsequently converted to a proportion relative to the good-every-day category (P-WTP). Consumers also answered a short demographic questionnaire. The four sensory scores, the MQ4 score and the P-WTP were analysed separately, as dependant variables in linear mixed effects models. The answers from the demographic questionnaire were included in the model as fixed effects. Overall, there were only small differences in consumer scores and P-WTP between demographic groups. Consumers who preferred their beef cooked medium or well-done scored beef higher, except in Poland, where the opposite trend was found. This may be because Polish consumers were more likely to prefer their beef cooked well-done, but samples were cooked medium for this group. There was a small positive relationship with the importance of beef in the diet, increasing sensory scores by about 4% in Poland and Northern Ireland. Men also scored beef about 2% higher than women for most sensory scores in most countries. In most countries, consumers were willing to pay between 150 and 200% more for premium beef, and there was a 50% penalty in value for unsatisfactory beef. After quality grade, by far the greatest influence on P-WTP was country of origin. Consumer age also had a small negative relationship with P-WTP. The results indicate that a single quality score could reliably describe the eating quality experienced by all consumers. In addition, if reliable quality information is delivered to consumers they will pay more for better quality beef, which would add value to the beef industry and encourage improvements in quality.
Untrained consumer assessment of the eating quality of beef: 1. A single composite score can predict beef quality grades
- S. P. F. Bonny, J.-F. Hocquette, D. W. Pethick, I. Legrand, J. Wierzbicki, P. Allen, L. J. Farmer, R. J. Polkinghorne, G. E. Gardner
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Quantifying consumer responses to beef across a broad range of demographics, nationalities and cooking methods is vitally important for any system evaluating beef eating quality. On the basis of previous work, it was expected that consumer scores would be highly accurate in determining quality grades for beef, thereby providing evidence that such a technique could be used to form the basis of and eating quality grading system for beef. Following the Australian MSA (Meat Standards Australia) testing protocols, over 19 000 consumers from Northern Ireland, Poland, Ireland, France and Australia tasted cooked beef samples, then allocated them to a quality grade; unsatisfactory, good-every-day, better-than-every-day and premium. The consumers also scored beef samples for tenderness, juiciness, flavour-liking and overall-liking. The beef was sourced from all countries involved in the study and cooked by four different cooking methods and to three different degrees of doneness, with each experimental group in the study consisting of a single cooking doneness within a cooking method for each country. For each experimental group, and for the data set as a whole, a linear discriminant function was calculated, using the four sensory scores which were used to predict the quality grade. This process was repeated using two conglomerate scores which are derived from weighting and combining the consumer sensory scores for tenderness, juiciness, flavour-liking and overall-liking, the original meat quality 4 score (oMQ4) (0.4, 0.1, 0.2, 0.3) and current meat quality 4 score (cMQ4) (0.3, 0.1, 0.3, 0.3). From the results of these analyses, the optimal weightings of the sensory scores to generate an ‘ideal meat quality 4 score (MQ4)’ for each country were calculated, and the MQ4 values that reflected the boundaries between the four quality grades were determined. The oMQ4 weightings were far more accurate in categorising European meat samples than the cMQ4 weightings, highlighting that tenderness is more important than flavour to the consumer when determining quality. The accuracy of the discriminant analysis to predict the consumer scored quality grades was similar across all consumer groups, 68%, and similar to previously reported values. These results demonstrate that this technique, as used in the MSA system, could be used to predict consumer assessment of beef eating quality and therefore to underpin a commercial eating quality guarantee for all European consumers.
European conformation and fat scores have no relationship with eating quality
- S. P. F. Bonny, D. W. Pethick, I. Legrand, J. Wierzbicki, P. Allen, L. J. Farmer, R. J. Polkinghorne, J.-F. Hocquette, G. E. Gardner
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European conformation and fat grades are a major factor determining carcass value throughout Europe. The relationships between these scores and sensory scores were investigated. A total of 3786 French, Polish and Irish consumers evaluated steaks, grilled to a medium doneness, according to protocols of the ‘Meat Standards Australia’ system, from 18 muscles representing 455 local, commercial cattle from commercial abattoirs. A mixed linear effects model was used for the analysis. There was a negative relationship between juiciness and European conformation score. For the other sensory scores, a maximum of three muscles out of a possible 18 demonstrated negative effects of conformation score on sensory scores. There was a positive effect of European fat score on three individual muscles. However, this was accounted for by marbling score. Thus, while the European carcass classification system may indicate yield, it has no consistent relationship with sensory scores at a carcass level that is suitable for use in a commercial system. The industry should consider using an additional system related to eating quality to aid in the determination of the monetary value of carcasses, rewarding eating quality in addition to yield.
The variation in the eating quality of beef from different sexes and breed classes cannot be completely explained by carcass measurements
- S. P. F. Bonny, J.-F. Hocquette, D. W. Pethick, L. J. Farmer, I. Legrand, J. Wierzbicki, P. Allen, R. J. Polkinghorne, G. E. Gardner
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Delivering beef of consistent quality to the consumer is vital for consumer satisfaction and will help to ensure demand and therefore profitability within the beef industry. In Australia, this is being tackled with Meat Standards Australia (MSA), which uses carcass traits and processing factors to deliver an individual eating quality guarantee to the consumer for 135 different ‘cut by cooking methods’ from each carcass. The carcass traits used in the MSA model, such as ossification score, carcass weight and marbling explain the majority of the differences between breeds and sexes. Therefore, it was expected that the model would predict with eating quality of bulls and dairy breeds with good accuracy. In total, 8128 muscle samples from 482 carcasses from France, Poland, Ireland and Northern Ireland were MSA graded at slaughter then evaluated for tenderness, juiciness, flavour liking and overall liking by untrained consumers, according to MSA protocols. The scores were weighted (0.3, 0.1, 0.3, 0.3) and combined to form a global eating quality (meat quality (MQ4)) score. The carcasses were grouped into one of the three breed categories: beef breeds, dairy breeds and crosses. The difference between the actual and the MSA-predicted MQ4 scores were analysed using a linear mixed effects model including fixed effects for carcass hang method, cook type, muscle type, sex, country, breed category and postmortem ageing period, and random terms for animal identification, consumer country and kill group. Bulls had lower MQ4 scores than steers and females and were predicted less accurately by the MSA model. Beef breeds had lower eating quality scores than dairy breeds and crosses for five out of the 16 muscles tested. Beef breeds were also over predicted in comparison with the cross and dairy breeds for six out of the 16 muscles tested. Therefore, even after accounting for differences in carcass traits, bulls still differ in eating quality when compared with females and steers. Breed also influenced eating quality beyond differences in carcass traits. However, in this case, it was only for certain muscles. This should be taken into account when estimating the eating quality of meat. In addition, the coefficients used by the Australian MSA model for some muscles, marbling score and ultimate pH do not exactly reflect the influence of these factors on eating quality in this data set, and if this system was to be applied to Europe then the coefficients for these muscles and covariates would need further investigation.
Ossification score is a better indicator of maturity related changes in eating quality than animal age
- S. P. F. Bonny, D. W. Pethick, I. Legrand, J. Wierzbicki, P. Allen, L. J. Farmer, R. J. Polkinghorne, J.-F. Hocquette, G. E. Gardner
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Ossification score and animal age are both used as proxies for maturity-related collagen crosslinking and consequently decreases in beef tenderness. Ossification score is strongly influenced by the hormonal status of the animal and may therefore better reflect physiological maturity and consequently eating quality. As part of a broader cross-European study, local consumers scored 18 different muscle types cooked in three ways from 482 carcasses with ages ranging from 590 to 6135 days and ossification scores ranging from 110 to 590. The data were studied across three different maturity ranges; the complete range of maturities, a lesser range and a more mature range. The lesser maturity group consisted of carcasses having either an ossification score of 200 or less or an age of 987 days or less with the remainder in the greater maturity group. The three different maturity ranges were analysed separately with a linear mixed effects model. Across all the data, and for the greater maturity group, animal age had a greater magnitude of effect on eating quality than ossification score. This is likely due to a loss of sensitivity in mature carcasses where ossification approached and even reached the maximum value. In contrast, age had no relationship with eating quality for the lesser maturity group, leaving ossification score as the more appropriate measure. Therefore ossification score is more appropriate for most commercial beef carcasses, however it is inadequate for carcasses with greater maturity such as cull cows. Both measures may therefore be required in models to predict eating quality over populations with a wide range in maturity.
Biochemical measurements of beef are a good predictor of untrained consumer sensory scores across muscles
- S. P. F. Bonny, G. E. Gardner, D. W. Pethick, I. Legrand, R. J. Polkinghorne, J. F. Hocquette
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The ability of the biochemical measurements, haem iron, intramuscular fat (IMF%), moisture content, and total, soluble and insoluble collagen contents, to predict untrained consumer sensory scores both across different muscles and within the same muscle from different carcasses were investigated. Sensory scores from 540 untrained French consumers (tenderness, flavour liking, juiciness and overall liking) were obtained for six muscles; outside (m. biceps femoris), topside (m. semimembranosus), striploin (m. longissimus thoracis), rump (m. gluteus medius), oyster blade (m. infraspinatus) and tenderloin (m. psoas major) from each of 18 French and 18 Australian cattle. The four sensory scores were weighted and combined into a single score termed MQ4, which was also analysed. All sensory scores were highly correlated with each other and with MQ4. This in part reflects the fact that MQ4 is derived from the consumer scores for tenderness, juiciness, flavour and overall liking and also reflects an interrelationship between the sensory scores themselves and in turn validates the use of the MQ4 term to reflect the scope of the consumer eating experience. When evaluated across the six different muscles, all biochemical measurements, except soluble collagen, had a significant effect on all of the sensory scores and MQ4. The average magnitude of impact of IMF%, haem iron, moisture content, total and insoluble collagen contents across the four different sensory scores are 34.9, 5.1, 7.2, 36.3 and 41.3, respectively. When evaluated within the same muscle, only IMF% and moisture content had a significant effect on overall liking (5.9 and 6.2, respectively) and flavour liking (6.1 and 6.4, respectively). These results indicate that in a commercial eating quality prediction model including muscle type, only IMF% or moisture content has the capacity to add any precision. However, all tested biochemical measurements, particularly IMF% and insoluble collagen contents, are strong predictors of eating quality when muscle type is not known. This demonstrates their potential usefulness in extrapolating the sensory data derived from these six muscles to other muscles with no sensory data, but with similar biochemical parameters, and therefore reducing the amount of future sensory testing required.
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- By H. Elliott Albers, Reut Avinun, Karen L. Bales, Jorge A. Barraza, Michael T. Bowen, Sunny K. Boyd, Heather K. Caldwell, Elena Choleris, Amy E. Clipperton-Allen, Bruce S. Cushing, Monica B. Dhakar, Riccardo Dore, Richard P. Ebstein, Craig F. Ferris, Sara M. Freeman, James L. Goodson, Joshua J. Green, Haruhiro Higashida, Eric Hollander, Salomon Israel, Martin Kavaliers, Keith M. Kendrick, Ariel Knafo, Yoav Litvin, Olga Lopatina, David Mankuta, Iain S. McGregor, Richard H. Melloni, Inga D. Neumann, Jerome H. Pagani, Cort A. Pedersen, Donald W. Pfaff, Anna Phan, Benjamin J. Ragen, Amina Sarwat, Idan Shalev, Erica L. Stevenson, Bonnie Taylor, Richmond R. Thompson, Florina Uzefovsky, Erwin H. van den Burg, James C. Walton, Scott R. Wersinger, Nurit Yirmiya, Larry J. Young, W. Scott Young, Paul J. Zak
- Edited by Elena Choleris, University of Guelph, Ontario, Donald W. Pfaff, Rockefeller University, New York, Martin Kavaliers, University of Western Ontario
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- Oxytocin, Vasopressin and Related Peptides in the Regulation of Behavior
- Published online:
- 05 April 2013
- Print publication:
- 11 April 2013, pp xi-xiv
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Whole body insulin responsiveness is higher in beef steers selected for increased muscling
- P. McGilchrist, D. W. Pethick, S. P. F. Bonny, P. L. Greenwood, G. E. Gardner
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The aim of this experiment was to evaluate the impact of selection for greater muscling on whole body insulin responsiveness in cattle, as reflected by greater uptake of glucose in response to constant insulin infusion and greater glucose disappearance following an intravenous glucose tolerance test. This study used 18-month-old steers from an Angus herd visually assessed and selected for divergence in muscling over 15 years. Eleven high-muscled (High), 10 low-muscled (Low) and 3 high-muscled steers, which were heterozygous for a myostatin polymorphism (HighHet), were infused with insulin using the hyperinsulineamic-euglyceamic clamp technique. Insulin was constantly infused at two levels, 0.6 μIU/kg per min and 6.0 μIU/kg per min. Glucose was concurrently infused to maintain euglyceamia and the steady state glucose infusion rate (SSGIR) indicated insulin responsiveness. An intravenous glucose tolerance test was also administered at 200 mg/kg live weight. Sixteen blood samples were collected from each animal between −30 and 130 min relative to the administration of intravenous glucose, plasma glucose and insulin concentration was determined in order to analyse insulin secretion and glucose disappearance. Insulin-like growth factor-1 (IGF-1) was also measured in basal plasma samples. At the low insulin infusion rate of 0.6 mU/kg per min, the SSGIR was 73% higher for the High muscling genotype animals when compared to the Low (P < 0.05). At the high insulin infusion rate of 6.0 mU/kg per min, these differences were proportionately less with the High and the HighHet genotypes having only 27% and 34% higher SSGIR (P < 0.05) than the Low-muscled genotype. The High-muscled cattle also had 30% higher plasma IGF-1 concentrations compared to the Low-muscled cattle. There was no effect of muscling genotype on basal insulin or basal glucose concentrations, glucose disappearance or insulin secretion following an intravenous glucose tolerance test. The increased whole body insulin responsiveness in combination with higher IGF-1 concentrations in the High-muscled steers is likely to initiate a greater level of protein synthesis, which may partially explain the increased muscle accretion in these animals.
Beef cattle selected for increased muscularity have a reduced muscle response and increased adipose tissue response to adrenaline
- P. McGilchrist, D. W. Pethick, S. P. F. Bonny, P. L. Greenwood, G. E. Gardner
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The aim of this experiment was to evaluate the impact of selection for greater muscling on the adrenaline responsiveness of muscle, adipose and liver tissue, as reflected by changes in plasma levels of the intermediary metabolites lactate, non-esterified fatty acids (NEFA) and glucose. This study used 18-month-old steers from an Angus herd visually assessed and selected for divergence in muscling for over 15 years. Ten low muscled (Low), 11 high muscled (High) and 3 high muscled heterozygotes for myostatin mutation (HighHet) steers were challenged with adrenaline doses ranging between 0.2 to 3.0 μg/kg live weight. For each challenge, 16 blood samples were taken between −30 and 130 min relative to adrenaline administration. Plasma was analysed for NEFA, lactate and glucose concentration and area under curve (AUC) over time was calculated to reflect the tissue responses to adrenaline. Sixteen basal plasma samples from each animal were also assayed for growth hormone. Muscle glycogen and lactate concentration were analysed from four muscle biopsies taken from the semimembranosus, semitendinosus and longissimus thoracis et lumborum of each animal at 14, 90 and 150 days on an ad libitum grain-based diet and at slaughter on day 157. In response to the adrenaline challenges, the High steers had 30% lower lactate AUC than the Low steers at challenges greater than 2 μg/kg live weight, indicating lower muscle responsiveness at the highest adrenaline doses. Aligning with this decrease in muscle response in the High animals were the muscle glycogen concentrations which were 6.1% higher in the High steers. These results suggest that selection for muscling could reduce the incidence of dark, firm, dry meat that is caused by low levels of glycogen at slaughter. At all levels of adrenaline challenge, the High steers had at least 30% greater NEFA AUC, indicating that their adipose tissue was more responsive to adrenaline, resulting in greater lipolysis. In agreement with this response, the High steers had a higher plasma growth hormone concentration, which is likely to have contributed to the increased lipolysis evident in these animals in response to adrenaline. This difference in lipolysis may in part explain the reduced fatness of muscular cattle. There was no effect of selection for muscling on liver responsiveness to adrenaline.
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- By Rose Teteki Abbey, K. C. Abraham, David Tuesday Adamo, LeRoy H. Aden, Efrain Agosto, Victor Aguilan, Gillian T. W. Ahlgren, Charanjit Kaur AjitSingh, Dorothy B E A Akoto, Giuseppe Alberigo, Daniel E. Albrecht, Ruth Albrecht, Daniel O. Aleshire, Urs Altermatt, Anand Amaladass, Michael Amaladoss, James N. Amanze, Lesley G. Anderson, Thomas C. Anderson, Victor Anderson, Hope S. Antone, María Pilar Aquino, Paula Arai, Victorio Araya Guillén, S. Wesley Ariarajah, Ellen T. Armour, Brett Gregory Armstrong, Atsuhiro Asano, Naim Stifan Ateek, Mahmoud Ayoub, John Alembillah Azumah, Mercedes L. García Bachmann, Irena Backus, J. Wayne Baker, Mieke Bal, Lewis V. Baldwin, William Barbieri, António Barbosa da Silva, David Basinger, Bolaji Olukemi Bateye, Oswald Bayer, Daniel H. Bays, Rosalie Beck, Nancy Elizabeth Bedford, Guy-Thomas Bedouelle, Chorbishop Seely Beggiani, Wolfgang Behringer, Christopher M. Bellitto, Byard Bennett, Harold V. Bennett, Teresa Berger, Miguel A. Bernad, Henley Bernard, Alan E. Bernstein, Jon L. Berquist, Johannes Beutler, Ana María Bidegain, Matthew P. Binkewicz, Jennifer Bird, Joseph Blenkinsopp, Dmytro Bondarenko, Paulo Bonfatti, Riet en Pim Bons-Storm, Jessica A. Boon, Marcus J. Borg, Mark Bosco, Peter C. Bouteneff, François Bovon, William D. Bowman, Paul S. Boyer, David Brakke, Richard E. Brantley, Marcus Braybrooke, Ian Breward, Ênio José da Costa Brito, Jewel Spears Brooker, Johannes Brosseder, Nicholas Canfield Read Brown, Robert F. Brown, Pamela K. Brubaker, Walter Brueggemann, Bishop Colin O. Buchanan, Stanley M. Burgess, Amy Nelson Burnett, J. Patout Burns, David B. Burrell, David Buttrick, James P. Byrd, Lavinia Byrne, Gerado Caetano, Marcos Caldas, Alkiviadis Calivas, William J. Callahan, Salvatore Calomino, Euan K. Cameron, William S. Campbell, Marcelo Ayres Camurça, Daniel F. Caner, Paul E. Capetz, Carlos F. Cardoza-Orlandi, Patrick W. Carey, Barbara Carvill, Hal Cauthron, Subhadra Mitra Channa, Mark D. Chapman, James H. Charlesworth, Kenneth R. Chase, Chen Zemin, Luciano Chianeque, Philip Chia Phin Yin, Francisca H. Chimhanda, Daniel Chiquete, John T. Chirban, Soobin Choi, Robert Choquette, Mita Choudhury, Gerald Christianson, John Chryssavgis, Sejong Chun, Esther Chung-Kim, Charles M. A. Clark, Elizabeth A. Clark, Sathianathan Clarke, Fred Cloud, John B. Cobb, W. Owen Cole, John A Coleman, John J. Collins, Sylvia Collins-Mayo, Paul K. Conkin, Beth A. Conklin, Sean Connolly, Demetrios J. Constantelos, Michael A. Conway, Paula M. Cooey, Austin Cooper, Michael L. Cooper-White, Pamela Cooper-White, L. William Countryman, Sérgio Coutinho, Pamela Couture, Shannon Craigo-Snell, James L. Crenshaw, David Crowner, Humberto Horacio Cucchetti, Lawrence S. Cunningham, Elizabeth Mason Currier, Emmanuel Cutrone, Mary L. Daniel, David D. Daniels, Robert Darden, Rolf Darge, Isaiah Dau, Jeffry C. Davis, Jane Dawson, Valentin Dedji, John W. de Gruchy, Paul DeHart, Wendy J. Deichmann Edwards, Miguel A. De La Torre, George E. Demacopoulos, Thomas de Mayo, Leah DeVun, Beatriz de Vasconcellos Dias, Dennis C. Dickerson, John M. Dillon, Luis Miguel Donatello, Igor Dorfmann-Lazarev, Susanna Drake, Jonathan A. Draper, N. Dreher Martin, Otto Dreydoppel, Angelyn Dries, A. J. Droge, Francis X. D'Sa, Marilyn Dunn, Nicole Wilkinson Duran, Rifaat Ebied, Mark J. Edwards, William H. Edwards, Leonard H. Ehrlich, Nancy L. Eiesland, Martin Elbel, J. Harold Ellens, Stephen Ellingson, Marvin M. Ellison, Robert Ellsberg, Jean Bethke Elshtain, Eldon Jay Epp, Peter C. Erb, Tassilo Erhardt, Maria Erling, Noel Leo Erskine, Gillian R. Evans, Virginia Fabella, Michael A. Fahey, Edward Farley, Margaret A. Farley, Wendy Farley, Robert Fastiggi, Seena Fazel, Duncan S. Ferguson, Helwar Figueroa, Paul Corby Finney, Kyriaki Karidoyanes FitzGerald, Thomas E. FitzGerald, John R. Fitzmier, Marie Therese Flanagan, Sabina Flanagan, Claude Flipo, Ronald B. Flowers, Carole Fontaine, David Ford, Mary Ford, Stephanie A. Ford, Jim Forest, William Franke, Robert M. Franklin, Ruth Franzén, Edward H. Friedman, Samuel Frouisou, Lorelei F. Fuchs, Jojo M. Fung, Inger Furseth, Richard R. Gaillardetz, Brandon Gallaher, China Galland, Mark Galli, Ismael García, Tharscisse Gatwa, Jean-Marie Gaudeul, Luis María Gavilanes del Castillo, Pavel L. Gavrilyuk, Volney P. Gay, Metropolitan Athanasios Geevargis, Kondothra M. George, Mary Gerhart, Simon Gikandi, Maurice Gilbert, Michael J. Gillgannon, Verónica Giménez Beliveau, Terryl Givens, Beth Glazier-McDonald, Philip Gleason, Menghun Goh, Brian Golding, Bishop Hilario M. Gomez, Michelle A. Gonzalez, Donald K. Gorrell, Roy Gottfried, Tamara Grdzelidze, Joel B. Green, Niels Henrik Gregersen, Cristina Grenholm, Herbert Griffiths, Eric W. Gritsch, Erich S. Gruen, Christoffer H. Grundmann, Paul H. Gundani, Jon P. Gunnemann, Petre Guran, Vidar L. Haanes, Jeremiah M. 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Yee, Viktor Yelensky, Yeo Khiok-Khng, Gustav K. K. Yeung, Angela Yiu, Amos Yong, Yong Ting Jin, You Bin, Youhanna Nessim Youssef, Eliana Yunes, Robert Michael Zaller, Valarie H. Ziegler, Barbara Brown Zikmund, Joyce Ann Zimmerman, Aurora Zlotnik, Zhuo Xinping
- Edited by Daniel Patte, Vanderbilt University, Tennessee
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- Book:
- The Cambridge Dictionary of Christianity
- Published online:
- 05 August 2012
- Print publication:
- 20 September 2010, pp xi-xliv
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Managing Incidental Findings in Human Subjects Research: Analysis and Recommendations
- Susan M. Wolf, Frances P. Lawrenz, Charles A. Nelson, Jeffrey P. Kahn, Mildred K. Cho, Ellen Wright Clayton, Joel G. Fletcher, Michael K. Georgieff, Dale Hammerschmidt, Kathy Hudson, Judy Illes, Vivek Kapur, Moira A. Keane, Barbara A. Koenig, Bonnie S. LeRoy, Elizabeth G. McFarland, Jordan Paradise, Lisa S. Parker, Sharon F. Terry, Brian Van Ness, Benjamin S. Wilfond
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- Journal of Law, Medicine & Ethics / Volume 36 / Issue 2 / Summer 2008
- Published online by Cambridge University Press:
- 01 January 2021, pp. 219-248
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- Summer 2008
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Researchers, institutional review boards (IRBs), participants in human subjects research, and their families face an important but largely neglected problem — how should incidental findings (IFs) be managed in human subjects research. If researchers unexpectedly stumble upon information of potential health or reproductive significance, should they seek expert evaluation, contact the participant’s physician, tell the research participant, or respond with some combination? What should consent forms and the entire consent process say about how IFs will be handled in research? What should IRBs require?