Estimation of tulathromycin depletion in plasma and milk after subcutaneous injection in lactating goats using a nonlinear mixed-effects pharmacokinetic modeling approach

Citation: Lin, Z. M., Cuneo, M., Rowe, J. D., Li, M. J., Tell, L. A., Allison, S., . . . Gehring, R. (2016). Estimation of tulathromycin depletion in plasma and milk after subcutaneous injection in lactating goats using a nonlinear mixed-effects pharmacokinetic modeling approach. Bmc Veterinary Research, 12, 10. https://doi.org/10.1186/s12917-016-0884-4Background: Extra-label use of tulathromycin in lactating goats is common and may cause violative residues in milk. The objective of this study was to develop a nonlinear mixed-effects pharmacokinetic (NLME-PK) model to estimate tulathromycin depletion in plasma and milk of lactating goats. Eight lactating goats received two subcutaneous injections of 2.5 mg/kg tulathromycin 7 days apart; blood and milk samples were analyzed for concentrations of tulathromycin and the common fragment of tulathromycin (i.e., the marker residue CP-60,300), respectively, using liquid chromatography mass spectrometry. Based on these new data and related literature data, a NLME-PK compartmental model with first-order absorption and elimination was used to model plasma concentrations and cumulative excreted amount in milk. Monte Carlo simulations with 100 replicates were performed to predict the time when the upper limit of the 95% confidence interval of milk concentrations was below the tolerance. Results: All animals were healthy throughout the study with normal appetite and milk production levels, and with mild-moderate injection-site reactions that diminished by the end of the study. The measured data showed that milk concentrations of the marker residue of tulathromycin were below the limit of detection (LOD = 1.8 ng/ml) 39 days after the second injection. A 2-compartment model with milk as an excretory compartment best described tulathromycin plasma and CP-60,300 milk pharmacokinetic data. The model-predicted data correlated with the measured data very well. The NLME-PK model estimated that tulathromycin plasma concentrations were below LOD (1.2 ng/ml) 43 days after a single injection, and 62 days after the second injection with a 95% confidence. These estimated times are much longer than the current meat withdrawal time recommendation of 18 days for tulathromycin in non-lactating cattle. Conclusions: The results suggest that twice subcutaneous injections of 2.5 mg/kg tulathromycin are a clinically safe extra-label alternative approach for treating pulmonary infections in lactating goats, but a prolonged withdrawal time of at least 39 days after the second injection should be considered to prevent violative residues in milk and any dairy goat being used for meat should have an extended meat withdrawal time

2019 international consensus on cardiopulmonary resuscitation and emergency cardiovascular care science with treatment recommendations : summary from the basic life support; advanced life support; pediatric life support; neonatal life support; education, implementation, and teams; and first aid task forces

The International Liaison Committee on Resuscitation has initiated a continuous review of new, peer-reviewed, published cardiopulmonary resuscitation science. This is the third annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations. It addresses the most recent published resuscitation evidence reviewed by International Liaison Committee on Resuscitation Task Force science experts. This summary addresses the role of cardiac arrest centers and dispatcher-assisted cardiopulmonary resuscitation, the role of extracorporeal cardiopulmonary resuscitation in adults and children, vasopressors in adults, advanced airway interventions in adults and children, targeted temperature management in children after cardiac arrest, initial oxygen concentration during resuscitation of newborns, and interventions for presyncope by first aid providers. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the certainty of the evidence on the basis of the Grading of Recommendations, Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence to Decision Framework Highlights sections. The task forces also listed priority knowledge gaps for further research

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

Morphometric characteristics of basal cell carcinoma peritumoral stroma varies among basal cell carcinoma subtypes

<p>Abstract</p> <p>Background</p> <p>The role that the peritumoral stroma plays in the growth of tumours is currently poorly understood. In this manuscript the morphometric characteristics of basal cell carcinoma subtypes and their associated peritumoral stromas are presented.</p> <p>Methods</p> <p>Ninety eight digitized basal cell carcinoma histology slides were categorized as infiltrative, nodular, or superficial subtypes, and were analysed using a combination of manual and computer-assisted approaches. The morphometric characteristics of the tumour nests and their associated peritumoral stroma were quantified, and the presence of a marked immune reaction or elastosis was noted.</p> <p>Results</p> <p>The tumour to stroma ratio was different among each tumour subtype. Elastosis was identified in a greater proportion of the infiltrative tumours.</p> <p>Conclusions</p> <p>Quantitative differences exist between the peritumoral stroma of basal cell carcinoma subtypes. Future work exploring the relation between these morphometric differences and biochemical variations in peritumoral stroma may further our understanding of the biology of carcinoma development.</p> <p>Trial Registration</p> <p>Not applicable.</p

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

Influence of the quality implementation of a physical education curriculum on the physical development and physical fitness of children

<p>Abstract</p> <p>Background</p> <p>This study was constructed as a comparison group pre-test/post-test quasi-experiment to assess the effect of the implementation of the PE curriculum by specialist PE teachers on children's physical development and physical fitness.</p> <p>Methods</p> <p>146 classes from 66 Slovenian primary schools were assigned to quasi-test (71) and quasi-control (75) groups. Data from the SLOFIT database was used to compare the differences in physical fitness and development between groups of children whose PE lessons were delivered by specialist PE teachers from the second grade onwards (quasi-test, n = 950) or by generalist teachers in all first three grades (quasi-control, n = 994). The Linear Mixed Model was used to test the influence of specialist PE teachers' teaching.</p> <p>Results</p> <p>The quasi-control group showed significantly lower improvement of physical fitness by -0.07 z-score units (95% CI -0.12 to 0.02) compared to the quasi-test group. A significant difference of -0.20 (-0.27 to -0.13) was observed in explosive strength, and of -0.15 (-0.23 to -0.08) in running speed, and in flexibility by -0.22 (-0.29 to -0.14). No significant differences in physical development were observed.</p> <p>Conclusions</p> <p>Specialist PE teachers were more successful than generalist teachers in achieving greater improvement of children's physical fitness, but no differences were observed in physical development of quasi-test and quasi-control group.</p

Ice-sheet collapse and sea-level rise at the Bølling warming 14,600 years ago

Past sea-level records provide invaluable information about the response of ice sheets to climate forcing. Some such records suggest that the last deglaciation was punctuated by a dramatic period of sea-level rise, of about 20 metres, in less than 500 years. Controversy about the amplitude and timing of this meltwater pulse (MWP-1A) has, however, led to uncertainty about the source of the melt water and its temporal and causal relationships with the abrupt climate changes of the deglaciation. Here we show that MWP-1A started no earlier than 14,650 years ago and ended before 14,310 years ago, making it coeval with the Bolling warming. Our results, based on corals drilled offshore from Tahiti during Integrated Ocean Drilling Project Expedition 310, reveal that the increase in sea level at Tahiti was between 12 and 22 metres, with a most probable value between 14 and 18 metres, establishing a significant meltwater contribution from the Southern Hemisphere. This implies that the rate of eustatic sea-level rise exceeded 40 millimetres per year during MWP-1A