A model-based approach to predict individual weight loss with semaglutide in people with overweight or obesity.

AIMS: To determine the relationship between exposure and weight-loss trajectories for the glucagon-like peptide-1 analogue semaglutide for weight management. MATERIALS AND METHODS: Data from one 52-week, phase 2, dose-ranging trial (once-daily subcutaneous semaglutide 0.05-0.4 mg) and two 68-week phase 3 trials (once-weekly subcutaneous semaglutide 2.4 mg) for weight management in people with overweight or obesity with or without type 2 diabetes were used to develop a population pharmacokinetic (PK) model describing semaglutide exposure. An exposure-response model describing weight change was then developed using baseline demographics, glycated haemoglobin and PK data during treatment. The ability of the exposure-response model to predict 1-year weight loss based on weight data collected at baseline and after up to 28 weeks of treatment, was assessed using three independent phase 3 trials. RESULTS: Based on population PK, exposure levels over time consistently explained the weight-loss trajectories across trials and dosing regimens. The exposure-response model had high precision and limited bias for predicting body weight loss at 1 year in independent datasets, with increased precision when data from later time points were included in the prediction. CONCLUSION: An exposure-response model has been established that quantitatively describes the relationship between systemic semaglutide exposure and weight loss and predicts weight-loss trajectories for people with overweight or obesity who are receiving semaglutide doses up to 2.4 mg once weekly.

Correction to: A bivariate genomic model with additive, dominance and inbreeding depression effects for sire line and three-way crossbred pigs.

An amendment to this paper has been published and can be accessed via the original article.

Impact of dose-escalation schemes and drug discontinuation on weight loss outcomes with liraglutide 3.0 mg: A model-based approach.

AIMS: To investigate the impact on weight loss of the treatment changes in overweight or obese people that may be needed in case of gastrointestinal (GI) tolerability issues during escalation of the glucagon-like peptide-1 analogue liraglutide. MATERIALS AND METHODS: The individual longitudinal body weight data from the main trial periods of three phase II/III trials in overweight or obese patients (56-week treatment with once-daily liraglutide 1.2, 1.8, 2.4 or 3.0 mg or placebo, n = 4952) were analysed using a non-linear mixed-effect modelling approach. Individual pharmacokinetic profiles were derived based on published pharmacokinetic models. Baseline body weight, baseline glycated haemoglobin (HbA1c), age, gender, diabetes status (no diabetes, prediabetes or type 2 diabetes), race and trial region were investigated as covariates. As a form of external validation, the model was used to predict the weight regain after treatment cessation at week 56 (data not included in model development). RESULTS: A pharmacokinetic/pharmacodynamic model provided an adequate description of the weight loss trajectories for all studied doses. Gender and diabetes status were identified as the most influential covariates, and an underlying seasonal weight fluctuation was identified. Slower than that recommended, one-week dose-escalation algorithms led up to 2 weeks slower initial weight loss but similar long-term weight loss trajectories. CONCLUSIONS: The relationship between liraglutide systemic exposure and weight loss was successfully established in overweight or obese people. The model could predict the time course of weight regain after treatment cessation and suggests that GI tolerability can be mitigated by slower escalation with only minor impact on the weight loss trajectory.

A bivariate genomic model with additive, dominance and inbreeding depression effects for sire line and three-way crossbred pigs.

BACKGROUND: Crossbreeding is widely used in pig production because of the benefits of heterosis effects and breed complementarity. Commonly, sire lines are bred for traits such as feed efficiency, growth and meat content, whereas maternal lines are also bred for reproduction and longevity traits, and the resulting three-way crossbred pigs are used for production of meat. The most important genetic basis for heterosis is dominance effects, e.g. removal of inbreeding depression. The aims of this study were to (1) present a modification of a previously developed model with additive, dominance and inbreeding depression genetic effects for analysis of data from a purebred sire line and three-way crossbred pigs; (2) based on this model, present equations for additive genetic variances, additive genetic covariance, and estimated breeding values (EBV) with associated accuracies for purebred and crossbred performances; (3) use the model to analyse four production traits, i.e. ultra-sound recorded backfat thickness (BF), conformation score (CONF), average daily gain (ADG), and feed conversion ratio (FCR), recorded on Danbred Duroc and Danbred Duroc-Landrace-Yorkshire crossbred pigs reared in the same environment; and (4) obtain estimates of genetic parameters, additive genetic correlations between purebred and crossbred performances, and EBV with associated accuracies for purebred and crossbred performances for this data set. RESULTS: Additive genetic correlations (with associated standard errors) between purebred and crossbred performances were equal to 0.96 (0.07), 0.83 (0.16), 0.75 (0.17), and 0.87 (0.18) for BF, CONF, ADG, and FCR, respectively. For BF, ADG, and FCR, the additive genetic variance was smaller for purebred performance than for crossbred performance, but for CONF the reverse was observed. EBV on Duroc boars were more accurate for purebred performance than for crossbred performance for BF, CONF and FCR, but not for ADG. CONCLUSIONS: Methodological developments led to equations for genetic (co)variances and EBV with associated accuracies for purebred and crossbred performances in a three-way crossbreeding system. As illustrated by the data analysis, these equations may be useful for implementation of genomic selection in this system.

Optimizing Dose-Finding Studies for Drug Combinations Based on Exposure-Response Models.

Combinations of pharmacological treatments are increasingly being investigated for potentially higher clinical benefit, especially when the combined drugs are expected to act via synergistic interactions. The clinical development of combination treatments is particularly challenging, particularly during the dose-selection phase, where a vast range of possible combination doses exists. The purpose of this work was to evaluate the added value of using optimal design for guiding the dose allocation in drug combination dose-finding studies as compared with a typical drug-combination trial. Optimizations were performed using local [D(s)-optimality] and global [ED(s)-optimality] optimal designs to maximize the precision of model parameters in a number of potential exposure-response (E-R) surfaces. A compound criterion [D(s)/V-optimality] was used to optimize the precision of model predictions in specific parts of the E-R surfaces. Optimal designs provided unbiased estimates and significantly improved the accuracy of results relative to the typical design. It was possible to improve the efficiency and overall parameter precision up to 7832% and 96.6% respectively. When the compound criterion was used, the probability to accurately identify the optimal dose-combination increased from 71% for the typical design up to 91%. These results indicate that optimal design methodology in tandem with E-R analyses is a beneficial tool that can be used for appropriate dose allocation in dose-finding studies for drug combinations.

Feasibility of Exposure-Response Analyses for Clinical Dose-Ranging Studies of Drug Combinations.

The exposure-response relationship of combinatory drug effects can be quantitatively described using pharmacodynamic interaction models, which can be used for the selection of optimal dose combinations. The aim of this simulation study was to evaluate the reliability of parameter estimates and the probability for accurate dose identification for various underlying exposure-response profiles, under a number of different phase II designs. An efficacy variable driven by the combined exposure of two theoretical compounds was simulated and model parameters were estimated using two different models, one estimating all parameters and one assuming that adequate previous knowledge for one drug is readily available. Estimation of all pharmacodynamic parameters under a realistic, in terms of sample size and study design, phase II trial, proved to be challenging. Inaccurate estimates were found in all exposure-response scenarios, except for situations where no pharmacodynamic interaction was present, with the drug potency and interaction parameters being the hardest to estimate. When previous knowledge of the exposure-response relationship of one of the monocomponents is available, such information should be utilized, as it enabled relevant improvements in parameter estimation and in correct dose identification. No general trends for classification of the performance of the tested study designs across different scenarios could be identified. This study shows that pharmacodynamic interactions models can be used for the exposure-response analysis of clinical endpoints especially when accompanied by appropriate dose selection in regard to the expected drug potencies and appropriate trial size and if information regarding the exposure-response profile of one monocomponent is available.

Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake.

Residual feed intake (RFI) is a complex trait that is economically important for livestock production; however, the genetic and biological mechanisms regulating RFI are largely unknown in pigs. Therefore, the study aimed to identify single nucleotide polymorphisms (SNPs), candidate genes and biological pathways involved in regulating RFI using Genome-wide association (GWA) and pathway analyses. A total of 596 Yorkshire boars with phenotypes for two different measures of RFI (RFI1 and 2) and 60k genotypic data was used. GWA analysis was performed using a univariate mixed model and 12 and 7 SNPs were found to be significantly associated with RFI1 and RFI2, respectively. Several genes such as xin actin-binding repeat-containing protein 2 (XIRP2),tetratricopeptide repeat domain 29 (TTC29),suppressor of glucose, autophagy associated 1 (SOGA1),MAS1,G-protein-coupled receptor (GPCR) kinase 5 (GRK5),prospero-homeobox protein 1 (PROX1),GPCR 155 (GPR155), and FYVE domain containing the 26 (ZFYVE26) were identified as putative candidates for RFI based on their genomic location in the vicinity of these SNPs. Genes located within 50 kbp of SNPs significantly associated with RFI and RFI2 (q-value ≤ 0.2) were subsequently used for pathway analyses. These analyses were performed by assigning genes to biological pathways and then testing the association of individual pathways with RFI using a Fisher's exact test. Metabolic pathway was significantly associated with both RFIs. Other biological pathways regulating phagosome, tight junctions, olfactory transduction, and insulin secretion were significantly associated with both RFI traits when relaxed threshold for cut-off p-value was used (p ≤ 0.05). These results implied porcine RFI is regulated by multiple biological mechanisms, although the metabolic processes might be the most important. Olfactory transduction pathway controlling the perception of feed via smell, insulin pathway controlling food intake might be important pathways for RFI. Furthermore, our study revealed key genes and genetic variants that control feed efficiency that could potentially be useful for genetic selection of more feed efficient pigs.

Genome-wide association and systems genetic analyses of residual feed intake, daily feed consumption, backfat and weight gain in pigs.

BACKGROUND: Feed efficiency is one of the major components determining costs of animal production. Residual feed intake (RFI) is defined as the difference between the observed and the expected feed intake given a certain production. Residual feed intake 1 (RFI1) was calculated based on regression of individual daily feed intake (DFI) on initial test weight and average daily gain. Residual feed intake 2 (RFI2) was as RFI1 except it was also regressed with respect to backfat (BF). It has been shown to be a sensitive and accurate measure for feed efficiency in livestock but knowledge of the genomic regions and mechanisms affecting RFI in pigs is lacking. The study aimed to identify genetic markers and candidate genes for RFI and its component traits as well as pathways associated with RFI in Danish Duroc boars by genome-wide associations and systems genetic analyses. RESULTS: Phenotypic and genotypic records (using the Illumina Porcine SNP60 BeadChip) were available on 1,272 boars. Fifteen and 12 loci were significantly associated (p < 1.52 × 10-6) with RFI1 and RFI2, respectively. Among them, 10 SNPs were significantly associated with both RFI1 and RFI2 implying the existence of common mechanisms controlling the two RFI measures. Significant QTL regions for component traits of RFI (DFI and BF) were detected on pig chromosome (SSC) 1 (for DFI) and 2 for (BF). The SNPs within MAP3K5 and PEX7 on SSC 1, ENSSSCG00000022338 on SSC 9, and DSCAM on SSC 13 might be interesting markers for both RFI measures. Functional annotation of genes in 0.5 Mb size flanking significant SNPs indicated regulation of protein and lipid metabolic process, gap junction, inositol phosphate metabolism and insulin signaling pathway are significant biological processes and pathways for RFI, respectively. CONCLUSIONS: The study detected novel genetic variants and QTLs on SSC 1, 8, 9, 13 and 18 for RFI and indicated significant biological processes and metabolic pathways involved in RFI. The study also detected novel QTLs for component traits of RFI. These results improve our knowledge of the genetic architecture and potential biological pathways underlying RFI; which would be useful for further investigations of key candidate genes for RFI and for development of biomarkers.

Prediction of enteric methane emissions from cattle.

Agriculture has a key role in food production worldwide and it is a major component of the gross domestic product of several countries. Livestock production is essential for the generation of high quality protein foods and the delivery of foods in regions where animal products are the main food source. Environmental impacts of livestock production have been examined for decades, but recently emission of methane from enteric fermentation has been targeted as a substantial greenhouse gas source. The quantification of methane emissions from livestock on a global scale relies on prediction models because measurements require specialized equipment and may be expensive. The predictive ability of current methane emission models remains poor. Moreover, the availability of information on livestock production systems has increased substantially over the years enabling the development of more detailed methane prediction models. In this study, we have developed and evaluated prediction models based on a large database of enteric methane emissions from North American dairy and beef cattle. Most probable models of various complexity levels were identified using a Bayesian model selection procedure and were fitted under a hierarchical setting. Energy intake, dietary fiber and lipid proportions, animal body weight and milk fat proportion were identified as key explanatory variables for predicting emissions. Models here developed substantially outperformed models currently used in national greenhouse gas inventories. Additionally, estimates of repeatability of methane emissions were lower than the ones from the literature and multicollinearity diagnostics suggested that prediction models are stable. In this context, we propose various enteric methane prediction models which require different levels of information availability and can be readily implemented in national greenhouse gas inventories of different complexity levels. The utilization of such models may reduce errors associated with prediction of methane and allow a better examination and representation of policies regulating emissions from cattle.

Genome-wide association study reveals genetic architecture of eating behavior in pigs and its implications for humans obesity by comparative mapping.

This study was aimed at identifying genomic regions controlling feeding behavior in Danish Duroc boars and its potential implications for eating behavior in humans. Data regarding individual daily feed intake (DFI), total daily time spent in feeder (TPD), number of daily visits to feeder (NVD), average duration of each visit (TPV), mean feed intake per visit (FPV) and mean feed intake rate (FR) were available for 1130 boars. All boars were genotyped using the Illumina Porcine SNP60 BeadChip. The association analyses were performed using the GenABEL package in the R program. Sixteen SNPs were found to have moderate genome-wide significance (p<5E-05) and 76 SNPs had suggestive (p<5E-04) association with feeding behavior traits. MSI2 gene on chromosome (SSC) 14 was very strongly associated with NVD. Thirty-six SNPs were located in genome regions where QTLs have previously been reported for behavior and/or feed intake traits in pigs. The regions: 64-65 Mb on SSC 1, 124-130 Mb on SSC 8, 63-68 Mb on SSC 11, 32-39 Mb and 59-60 Mb on SSC 12 harbored several signifcant SNPs. Synapse genes (GABRR2, PPP1R9B, SYT1, GABRR1, CADPS2, DLGAP2 and GOPC), dephosphorylation genes (PPM1E, DAPP1, PTPN18, PTPRZ1, PTPN4, MTMR4 and RNGTT) and positive regulation of peptide secretion genes (GHRH, NNAT and TCF7L2) were highly significantly associated with feeding behavior traits. This is the first GWAS to identify genetic variants and biological mechanisms for eating behavior in pigs and these results are important for genetic improvement of pig feed efficiency. We have also conducted pig-human comparative gene mapping to reveal key genomic regions and/or genes on the human genome that may influence eating behavior in human beings and consequently affect the development of obesity and metabolic syndrome. This is the first translational genomics study of its kind to report potential candidate genes for eating behavior in humans.

The interactive effects of selenomethionine and methylmercury on their absorption, disposition, and elimination in juvenile white sturgeon.

Selenium (Se) and mercury (Hg) are prevalent pollutants of industrialized watersheds. However, when co-administered, Se has protective effects on organisms from Hg. The mechanism is not fully understood, but it is thought that Se reduces Hg availability, either by forming biologically inert complexes and/or associating with selenoproteins. Despite concerns with aquatic contaminations, relatively little information is available on the interaction in aquatic organisms. In the present study, the interactive effects of Se and Hg on their absorption, disposition, and elimination were examined in juvenile white sturgeon, a benthic fish species at high risk to exposures of both contaminants. Selenium and Hg were provided as L-selenomethionine (SeMet) and methylmercury (MeHg), respectively. Groups of 10 sturgeon were orally intubated with a single dose of either 0 (control), SeMet (500 µg Se/kg body weight; BW), MeHg (850 µg Hg/kg BW), or their combination (Se/Hg; 500 µg Se/kg and 850 µg Hg/kg BW). The blood was repeatedly sampled and urine collected from the fish, over a 48 h post intubation period. At 48 h, the fish were sacrificed for Se and Hg tissue concentration and distribution. The co-administration of SeMet and MeHg significantly (p<0.05) lowered blood concentrations of both Se and Hg and tissue Se concentrations. Similarly, assimilation of Se and Hg was also reduced significantly. The interaction has a more quantitative effect on Se metabolism because the reduction in the overall tissue Se is a consequence of reduced Se absorption at the gut and not from the metabolic effects after absorption. In contrast, given the pulse increase in blood Hg concentration, tissue redistribution, and increased urinary elimination, the interactive effect on tissue Hg concentration is likely to be post-absorption. Even in the absence of exogenous SeMet, Se and Hg co-accumulated in tissue at a Se:Hg molar ratio greater than 1. Thus, similar to mammals, maintaining at least a 1:1 molar ratio of Se and Hg is of great physiological importance in the white sturgeon. Interestingly, SeMet did not divert Hg from the brain. Allocation of Se from the kidneys may have occurred in order to maintain the high Se:Hg molar ratios in the brain of white sturgeon. In the current study, the combined use of kinetic analysis and that of the conventional approach of measuring tissue concentration changes provided a comprehensive understanding of the interactive effect of SeMet and MeHg on their respective metabolic processes in juvenile white sturgeon.

Absorption, distribution, and elimination of graded oral doses of methylmercury in juvenile white sturgeon.

Mercury (Hg) is toxic and is released into the environment from a wide variety of anthropogenic sources. Methylmercury (MeHg), a product of microbial methylation, enables rapid Hg bioaccumulation and biomagnification in the biota. Methylmercury is sequestered and made available to the rest of the biota through the benthic-detrital component leading to the high risk of exposure to benthic fish species, such as white sturgeon (Acipenser transmontanus). In the present study, a combined technique of stomach intubation, dorsal aorta cannulation, and urinary catheterization was utilized to characterize the absorption, distribution, and elimination of Hg in white sturgeon over a 48h exposure. Mercury, as methylmercury chloride, at either 0, 250, 500, or 1000 µg Hg/kg body weight, was orally intubated into white sturgeon, in groups of five. The blood was repeatedly sampled and urine collected from the fish over the 48h post intubation period, and at 48h, the fish were sacrificed for Hg tissue concentration and distribution determinations. The fractional rate of absorption (K), blood Hg concentration (µg/ml), tissue concentration (µg/g dry weight) and distribution (%), and urinary Hg elimination flux (µg/kg/h) are significantly different (p<0.05) among the MeHg doses. Complete blood uptake of Hg was observed in all MeHg treated fish by 12h. The maximal observed blood Hg concentration peaks are 0.56±0.02, 0.70±0.02, and 2.19±0.07 µg/ml (mean±SEM) for the 250, 500, and 1000 µgHg/kg body weight dose groups, respectively. Changes in blood Hg profiles can be described by a monomolecular function in all of the MeHg treated fish. The Hg concentration asymptote (A) and K are dose dependent. The relationship between A and the intubation dose, however, is nonlinear. Mercury levels in certain tissues are comparable to field data and longer-term study, indicating that the lower doses used in the current study are ecologically relevant for the species. Tissue Hg concentrations are in the following decreasing order: gastro-intestinal tract>kidney>spleen>gill>heart>liver>brain>white muscle and remaining whole body. At 48h, Hg was found to be preferentially distributed to metabolically active tissues. Digestibility is highest at the lowest MeHg dose. Measurable urinary Hg was observed in the fish treated with the highest MeHg dose, and a significant increase in the elimination flux was observed between 3 and 12h post intubation.

Animal production for efficient phosphate utilization: from optimized feed to high efficiency livestock.

Phosphorus (P) is an essential nutrient for livestock but its efficiency of utilization is below 40%, contributing to environmental issues. In this review, we summarize recent approaches to optimize P availability in livestock diets and improve its utilization efficiency. Phase feeding could potentially reduce P excretion by 20%. Addition of phytase enzymes to diets increased P availability from 42 to 95%. Low phytate transgenic plants and transgenic animals increased P availability by 14% and 52-99%, respectively. In practice, a combination of phase feeding and enzymes has the highest potential for P reduction but legislation and ethics implications will prevent using transgenic animals in the short term. Functional and nutritional genomics may provide tools to improve efficiency in the future.

Evaluation of coronary band temperatures in healthy horses.

OBJECTIVE: To measure coronary band temperature (CBT) in healthy horses fed high-fructan or low-carbohydrate diets and to analyze the association of CBT with diet, time of day, and ambient temperature. ANIMALS: 6 healthy horses. PROCEDURES: Horses were fed 3 diets (treatment 1, 1 g of fructan/kg fed daily in the morning; treatment 2, 1 g of fructan/kg fed daily in the afternoon; and treatment 3, a low-carbohydrate [7.2%] diet) in a 3 × 3 Latin square study design. For each horse, the CBT of all 4 limbs as well as rectal and ambient temperatures were recorded by use of infrared thermometry and standard thermometers hourly from 8 am to 10 pm for 4 consecutive days after the initiation of each diet. Each horse received each diet, and there was a 10-day washout period between each diet change. Data were analyzed by use of a mixed linear model. RESULTS: 4,320 CBTs were obtained from the 6 horses. The CBT ranged from 9.6° to 35.5°C. Coronary band temperature followed a diurnal pattern and was positively associated with ambient temperature but was not associated with diet. CONCLUSIONS AND CLINICAL RELEVANCE: CBT of healthy horses varied significantly during the day and among limbs. These results should be considered whenever increased CBT is used as an indication of incipient laminitis or in other clinical investigations.

Selenocompounds in juvenile white sturgeon: evaluating blood, tissue, and urine selenium concentrations after a single oral dose.

Selenium (Se) is an essential micronutrient for all vertebrates, however, at environmental relevant levels, it is a potent toxin. In the San Francisco Bay-Delta, white sturgeon, an ancient Chondrostean fish of high ecological and economic value, is at risk to Se exposure. The present study is the first to examine the uptake, distribution, and excretion of various selenocompounds in white sturgeon. A combined technique of stomach intubation, dorsal aorta cannulation, and urinary catheterization was utilized, in this study, to characterize the short-term effects of Se in the forms of sodium-selenate (Selenate), sodium-selenite (Selenite), selenocystine (SeCys), l-selenomethionine (SeMet), Se-methylseleno-l-cysteine (MSeCys), and selenoyeast (SeYeast). An ecologically relevant dose of Se (∼500 µg/kg body weight) was intubated into groups of 5 juvenile white sturgeon. Blood and urine samples were repeatedly collected over the 48 h post intubation period and fish were sacrificed for Se tissue concentration and distribution at 48 h. The tissue concentration and distribution, blood concentrations, and urinary elimination of Se significantly differ (p ≤ 0.05) among forms. In general, organic selenocompounds maintain higher blood concentrations, with SeMeCys maintaining the highest area under the curve (66.3 ± 8.7 and 9.3 ± 1.0 µg h/ml) and maximum Se concentration in blood (2.3 ± 0.2 and 0.4 ± 0.2 µg/ml) in both the protein and non-protein bound fractions, respectively. Selenate, however, did not result in significant increase of Se concentration, compared with the control, in the protein-bound blood fraction. Regardless of source, Se is preferentially distributed into metabolically active tissues, with the SeMet treated fish achieving the highest concentration in most tissues. In contrast, Selenite has very similar blood concentrations and tissue distribution profile to SeCys and SeYeast. From blood and tissue Se concentrations, Selenate is not stored in blood, but taken up rapidly by the liver and white muscle. Urinary elimination of Se is form dependent and peaks between 3 and 12 h post intubation. A basic understanding of the overall Se absorption, distribution, and elimination is provided through monitoring tissue Se concentrations, however, conclusions regarding to the dynamics and the specific processes of Se metabolism can only be inferred, in the absence of kinetic information.

Selenocompounds in juvenile white sturgeon: estimating absorption, disposition, and elimination of selenium using Bayesian hierarchical modeling.

The biological function of selenium (Se) is determined by its form and concentration. Selenium is an essential micronutrient for all vertebrates, however, at environmental levels, it is a potent toxin. In the San Francisco Bay-Delta, Se pollution threatens top predatory fish, including white sturgeon. A multi-compartmental Bayesian hierarchical model was developed to estimate the fractional rates of absorption, disposition, and elimination of selenocompounds, in white sturgeon, from tissue measurements obtained in a previous study (Huang et al., 2012). This modeling methodology allows for a population based approach to estimate kinetic physiological parameters in white sturgeon. Briefly, thirty juvenile white sturgeon (five per treatment) were orally intubated with a control (no selenium) or a single dose of Se (500 µg Se/kg body weight) in the form of one inorganic (Selenite) or four organic selenocompounds: selenocystine (SeCys), l-selenomethionine (SeMet), Se-methylseleno-l-cysteine (MSeCys), or selenoyeast (SeYeast). Blood and urine Se were measured at intervals throughout the 48h post intubation period and eight tissues were sampled at 48 h. The model is composed of four state variables, conceptually the gut (Q1), blood (Q2), and tissue (Q3); and urine (Q0), all in units of µg Se. Six kinetics parameters were estimated: the fractional rates [1/h] of absorption, tissue disposition, tissue release, and urinary elimination (k12, k23, k32, and k20), the proportion of the absorbed dose eliminated through the urine (f20), and the distribution blood volume (V; percent body weight, BW). The parameter k12 was higher in sturgeon given the organic Se forms, in the descending order of MSeCys > SeMet > SeCys > Selenite > SeYeast. The parameters k23 and k32 followed similar patterns, and f20 was lowest in fish given MSeCys. Selenium form did not affect k20 or V. The parameter differences observed can be attributed to the different mechanisms of transmucosal transport, metabolic reduction, and storage of the Se forms, which, in general, appear to be similar to that in mammals. We have demonstrated that the Bayesian approach is a powerful tool for integrating quantitative information from a study with sparse blood and urinary measurements and tissue concentrations from a single time point, while providing a full characterization of parameter variability. The model permits the quantitative mechanistic interpretation and predictions of Se absorption, disposition, and elimination processes. Furthermore, the model represents a first step towards population based physiological toxicokinetic modeling of Se in white sturgeon.

Quantitative computed tomography evaluation of pulmonary disease.

Objective assessment of pulmonary disease from computed tomography (CT) examinations is desirable but difficult. When such assessments can be made, it is important that they are related to some part of the pathophysiologic process present. Herein we propose that automated volume histogram analysis can yield data that allow differentiation of normal from abnormal lung, and that the magnitude of disease will have an association with objective CT indices. Data from pulmonary CT images from 34 foxes (six uninfected controls and 28 infected with Angiostrongylus vasorum, subdivided by age and infective dose) were available. Lung tissue was segmented from surrounding tissue using an automated segmentation method. A volume histogram showing voxel frequency for each CT number in the range -1024 to -250 HU was created from the entire image stack from each fox. Using these data, the inter-quartile range and the CT number at the 95th percentile were determined. The results showed that segmentation could be readily achieved but that areas of severely diseased lung were excluded. Based on two-way analysis of variance for both the inter-quartile range and the CT number at the 95th percentile, both quantities were significantly affected by the infection status of the animal and were related to worm burden (P < 0.001). The study shows that this form of analysis is readily achieved and provides quantitative data that can be used to assess disease severity, progression, and response to treatment.

Hounsfield Unit dynamics of adipose tissue and non-adipose soft tissues in growing pigs.

Changes in the Hounsfield Unit value of adipose tissue and of non-adipose soft tissue during growth are poorly documented. This study examines the HU of these tissues in growing pigs. Computer tomography scans were made in nine growing pigs on three occasions, approximately four weeks apart. Average body weight was 51, 94, and 121 kg for each successive scan. Images from the level of the diaphragm to the hips were analyzed. The mean HU and its standard deviation, for adipose tissue and for non-adipose soft tissues was determined for each pig. The mean adipose tissue HU for all pigs was -90, -98 and -101 on the first, middle and last scans, respectively. Corresponding HU values for non-adipose soft tissues were, 52, 51 and 49. There was a significant difference (p<0.01) between HU at each scan time for each set of tissues.

Changes in the relative thickness of individual subcutaneous adipose tissue layers in growing pigs.

BACKGROUND: The thickness of the subcutaneous fat layer is an important parameter at all stages of pig production. It is used to inform decisions on dietary requirements to optimize growth, in gilts to promote longevity and finally to assist in the calculation of payments to producers that allow for general adiposity. Currently for reasons of tradition and ease, total adipose thickness measurements are made at one or multiple sites although it has been long recognized that up to three well defined layers (outer (L1), middle (L2), and inner (L3)) may be present to make up the total. Various features and properties of these layers have been described. This paper examines the contribution of each layer to total adipose thickness at three time points and describes the change in thickness of each layer per unit change in body weight in normal growing pigs. METHODS: A group of nine pigs was examined using 14 MHz linear array transducer on three separate occasions. The average weight was 51, 94 and 124 kg for each successive scan. The time between scanning was approximately 4 weeks. The proportion of each layer to total thickness was modeled statistically with scan session as a variable and the change in absolute thickness of each layer per unit change in body weight was modeled in a random regression model. RESULTS: There was a significant change in ratios between scans for the middle and inner layers (P < 0.001). The significant changes were seen between the first and second, and between the first and final, scan sessions. The change in thickness per unit change in body weight was greatest for L2, followed by L1 and L3. CONCLUSION: These results demonstrate that subcutaneous adipose layers grow at different rates relative to each other and to change in body weight and indicate that ultrasound can be used to track these differences.