Responses in randomised groups of healthy, adult Labrador retrievers fed grain-free diets with high legume inclusion for 30 days display commonalities with dogs with suspected dilated cardiomyopathy.

Early responses in healthy adult dogs fed grain-free diets with high inclusion of split peas (20%) and lentils (40%) that may lead to canine diet-induced dilated cardiomyopathy (DCM) were investigated. To help understand the clinical relevance of the findings, a survey of electronic health records (EHR) was conducted of dogs with and without suspected DCM for comparison. Control and Test diets were fed to Labrador retriever dogs for 30 days (n = 5 and 6, respectively). Blood and urine samples collected at baseline and days 3, 14 and 28/30 were analyzed for hematology, clinical biochemistry and taurine concentrations. The EHRs of dogs at Banfield® Pet Hospitals in the 2-year period 2018-2019 were surveyed, revealing 420 dogs diagnosed with DCM, which were compared with 420 breed, gender and age-matched healthy control dogs. Compared to baseline values, feeding the Test diet for 28 days caused progressive, significant (p < 0.001) decreases in red blood cell counts (RBC), hematocrit and total hemoglobin by 7.7, 8.3 and 6.3%, respectively, and a 41.8% increase in plasma inorganic phosphate. Commonalities in these parameters were observed in clinical DCM cases. Regarding taurine status, Test dogs transiently increased whole-blood (23.4%) and plasma (47.7%) concentrations on day 14, while taurine:creatinine ratio in fresh urine and taurine in pooled urine were reduced by 77 and 78%, respectively, on day 28/30. Thus grain-free, legume-rich Test diets caused reduced RBC and hyperphosphatemia, findings also indicated in dogs with suspected DCM. Changes in taurine metabolism were indicated. The data will aid in generating hypotheses for future studies.

Adaptations Supporting Plasma Methionine on a Limited-Methionine, High-Cystine Diet Alter the Canine Plasma Metabolome Consistent with Interventions that Extend Life Span in Other Species.

BACKGROUND: Using indicator amino acid oxidation methodology, the mean dietary requirement of adult dogs for methionine (Met) was estimated to be ∼66% of the current recommended allowance. Dogs fed a diet formulated to provide the estimated mean Met requirement for 32 wk maintained plasma Met, seemingly supported by betaine oxidation. OBJECTIVE: To gain a better understanding of the metabolic changes that were associated with supporting plasma Met when dogs were fed a limited Met diet over 32 wk, we analyzed plasma samples taken from that study using a data-driven metabolomics approach. METHODS: Labrador retrievers (20 females/13 males; mean age: 4.9 y; range: 2.0-7.9 y) were fed semi-purified, nutritionally complete diets. After 4 wk of feeding a control diet (DL-Met; 1.37 g/1000 kcal), 17 dogs remained on this diet and 16 were transitioned to a test diet formulated to the estimated mean Met requirement (0.55 g/1000 kcal), with dietary total sulfur amino acid maintained with additional l-cystine (Cys). Dogs were individually fed diets to maintain a stable body weight at an ideal body condition score for 32 wk. Plasma samples from fasted blood collected at baseline and 8 and 32 wk were analyzed using untargeted metabolic profiling. RESULTS: Analysis of metabolites (n = 593) confirmed our primary findings (increased Met, betaine, and dimethylglycine). Metabolite changes consistent with repartitioning choline to support Met cycling included reduced pools of lipids derived via phosphatidylethanolamine N-methyltransferase and enhanced fatty acid oxidation. Some changes were consistent with metabolomics studies reported in other species that used interventions known to extend life span (caloric- and Met-restricted diets or feeding strategy). CONCLUSIONS: Changes in the plasma metabolome were consistent with reported adaptations to support Met-dependent activities. We propose that feeding a limited-Met, high-Cys diet using the estimated mean Met requirement in adult Labrador retrievers alters regulation of the Met cycle, thereby altering metabolism, similar to interventions that extend life span.

Rapid Reconstitution of the Fecal Microbiome after Extended Diet-Induced Changes Indicates a Stable Gut Microbiome in Healthy Adult Dogs.

The gut microbiome has an important role in health, and diet represents a key lever for shaping the gut microbiome across all stages of life. Maternal milk consumption in neonates leads to long-term health effects, indicating that pliability in the infant gut microbiome in response to diet can drive enduring change. The ability of diet to drive lasting changes in the adult gut microbiome is less understood. We studied the effect of an extreme dietary shift on the fecal microbiome of 46 Labrador retriever dogs (mean age, 4.6 years) over 11 months. Dogs were fed a nutritionally complete, commercially available complex diet (CD) for a minimum of 5 weeks, followed by highly purified diets (PDs) for 36 weeks, and the initial CD for at least a further 4 weeks. Fecal samples were collected at regular intervals for DNA extraction. By analyzing 16S rRNA genes and the metagenomes, we observed minor effects on microbial diversity but significant changes in bacterial taxa and genetic potential when a PD was fed. Specifically, metagenomics identified an enrichment of quinone- and GABA-related pathways on PD, providing insights into dietary effects on cross-feeding strategies impacting community structure. When dogs returned to the CD, no significant differences were found with the initial time point. These findings are consistent with the gut microbiome being rapidly adaptable but capable of being reconstituted when provided with similar diets. These data highlight that long-term changes in the adult dog gut microbiome may only be achieved through long-term maintenance on a specified diet, rather than through feeding a transitionary diet.IMPORTANCE Diet can influence the adult gut microbiome (the community of bacteria) and health outcomes, but the ability to make changes persisting beyond feeding of a particular diet is poorly understood. We investigated whether feeding highly purified diets to adult dogs for 36 weeks would alter bacterial populations sufficiently to result in a persistent change following the dogs' return to a commercial diet. As expected, the microbiome changed when the purified diet was fed, but the original microbiome was reconstituted within weeks of the dogs returning to the commercial diet. The significance of these findings is in identifying an intrinsic stability of the host microbiome in healthy dogs, suggesting that dietary changes to support adult dog health through modifying the gut microbiome may be achieved only through maintenance on a specified diet, rather than through feeding transitionary diets.

Short-term determination and long-term evaluation of the dietary methionine requirement in adult dogs.

Methionine, an essential sulphur-containing amino acid (SAA), plays an integral role in many metabolic processes. Evidence for the methionine requirements of adult dogs is limited, and we employed the indicator amino acid oxidation (IAAO) method to estimate dietary methionine requirements in Labrador retrievers (n 21). Using semi-purified diets, the mean requirement was 0·55 (95 % CI 0·41, 0·71) g/4184 kJ. In a subsequent parallel design study, three groups of adult Labrador retrievers (n 52) were fed semi-purified diets with 0·55 g/4184 kJ (test diet 1), 0·71 g/4184 kJ (test diet 2) or 1·37 g/4184 kJ (control diet) of methionine for 32 weeks to assess the long-term consequences of feeding. The total SAA content (2·68 g/4184 kJ) was maintained through dietary supplementation of cystine. Plasma methionine did not decrease in test group and increased significantly on test diet 1 in weeks 8 and 16 compared with control. Reducing dietary methionine did not have a significant effect on whole blood, plasma or urinary taurine or plasma N-terminal pro B-type natriuretic peptide. Significant effects in both test diets were observed for cholesterol, betaine and dimethylglycine. In conclusion, feeding methionine at the IAAO-estimated mean was sufficient to maintain plasma methionine over 32 weeks when total SAA was maintained. However, choline oxidation may have increased to support plasma methionine and have additional consequences for lipid metabolism. While the IAAO can be employed to assess essential amino acid requirements, such as methionine in the dog using semi-purified diets, further work is required to establish safe levels for commercial diet formats.

The Significance of Environmental Attributes as Indicators of the Life Cycle Environmental Impacts of Packaging and Food Service Ware.

The environmental impacts of packaging and food service ware (FSW) are increasingly the subject of government policy, public discourse, and industry commitments. While some consideration is given to reducing the impacts of packaging across its entire life cycle, most of the focus is on packaging waste or feedstock substitution. Efforts typically focus on specific packaging characteristics, or material attributes, commonly perceived to be environmentally preferable. This article summarizes an extensive meta-review of existing published literature that was performed to determine whether the material attributes recyclability, recycled content, compostability, and biobased, commonly considered to be environmentally beneficial, correlate with lower net environmental impacts across the full life cycle of the packaging and FSW. Seventy-one unique life cycle assessment (LCA) studies that quantify the environmental impacts throughout the entire life cycle of packaging and FSW were analyzed. These studies included over 5000 comparisons for 13 impact categories commonly analyzed in LCA studies. The results from the meta-review identified a number of instances where material attributes do not correlate with environmental benefits for packaging and FSW. Rather, other characteristics such as material choice or mass of the packaging/FSW products can have higher influence in determining life cycle impacts.

Impact of dietary macronutrient profile on feline body weight is not consistent with the protein leverage hypothesis.

The protein leverage hypothesis proposes that the need to prioritise protein intake drives excess energy intake (EI) when the dietary ratio of protein to fat and carbohydrate is reduced. We hypothesised that cats may become prone to overconsuming energy content when moderate protein diets were offered, and considered the potential influence of fat and carbohydrate on intake. To determine the effect of dietary protein and macronutrient profile (MNP) on EI, weight and body composition, cats (1-4 years) were offered food in excess of energy requirements (ER). A total of six diets were formulated, containing moderate (approximately 7 % w/w; approximately 22 % metabolisable energy (ME)) or high (approximately 10 % w/w; approximately 46 % ME) protein and varying levels of carbohydrate and fat. For 4 weeks, 120 cats were offered 100 % of their individual ER of a diet at the MNP selected by adult cats (50:40:10 protein energy ratio:fat energy ratio:carbohydrate energy ratio). EI, body weight (BW), body composition, activity and palatability were measured. Subsequently, cats were offered one of the six diets at 200 % of their individual ER for 4 weeks when measurements were repeated. Cats offered excess high protein diets had higher EI (kJ/kg) throughout, but at 4 weeks BW was not significantly different to baseline. Cats offered excess moderate protein diets reduced EI and gradually lost weight (average loss of 0·358 (99 % CI 0·388, 0·328) kg), irrespective of fat:carbohydrate and initial palatability. The data do not support the protein leverage hypothesis. Furthermore, cats were able to adapt intake of a wet diet with high protein in an overfeeding environment within 28 d.

Adult dogs are capable of regulating calcium balance, with no adverse effects on health, when fed a high-calcium diet.

Although the implications of long-term high Ca intakes have been well documented in growing dogs, the health consequences of Ca excess in adult dogs remain to be established. To evaluate the impact of feeding a diet containing 7·1 g/4184 kJ (1000 kcal) Ca for 40 weeks on Ca balance and health parameters in adult dogs, eighteen neutered adult Labrador Retrievers, (nine males and nine females) aged 2·5-7·4 years were randomised to one of two customised diets for 40 weeks. The diets were manufactured according to similar nutritional specifications, with the exception of Ca and P levels. The diets provided 1·7 and 7·1 g/4184 kJ (1000 kcal) (200(SD26) and 881(SD145) mg/kg body weight0·75 per d, respectively) Ca, respectively, with a Ca:P ratio of 1·6. Clinical examinations, ultrasound scans, radiographs, health parameters, metabolic effects and mineral balance were recorded at baseline and at 8-week intervals throughout the study. Dogs in both groups were healthy throughout the trial without evidence of urinary, renal or orthopaedic disease. In addition, there were no clinically relevant changes in any of the measures made in either group (all P>0·05). The high-Ca diet resulted in a 3·3-fold increase in faecal Ca excretion (P0·05). Ca intakes of up to 7·1 g/4184 kJ (1000 kcal) are well tolerated over a period of 40 weeks, with no adverse effects that could be attributed to the diet or to a high mineral intake.

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data.

BACKGROUND: Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machine learning pipelines for omics data is feature selection, which is used to reduce the raw high-dimensional data into a tractable number of features. Feature selection needs to balance the objective of using as few features as possible, while maintaining high predictive power. This balance is crucial when the goal of data analysis is the identification of highly accurate but small panels of biomarkers with potential clinical utility. In this paper we propose a heuristic for the selection of very small feature subsets, via an iterative feature elimination process that is guided by rule-based machine learning, called RGIFE (Rule-guided Iterative Feature Elimination). We use this heuristic to identify putative biomarkers of osteoarthritis (OA), articular cartilage degradation and synovial inflammation, using both proteomic and transcriptomic datasets. RESULTS AND DISCUSSION: Our RGIFE heuristic increased the classification accuracies achieved for all datasets when no feature selection is used, and performed well in a comparison with other feature selection methods. Using this method the datasets were reduced to a smaller number of genes or proteins, including those known to be relevant to OA, cartilage degradation and joint inflammation. The results have shown the RGIFE feature reduction method to be suitable for analysing both proteomic and transcriptomics data. Methods that generate large 'omics' datasets are increasingly being used in the area of rheumatology. CONCLUSIONS: Feature reduction methods are advantageous for the analysis of omics data in the field of rheumatology, as the applications of such techniques are likely to result in improvements in diagnosis, treatment and drug discovery.

Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning.

BACKGROUND: Osteoarthritis (OA) is an inflammatory disease of synovial joints involving the loss and degeneration of articular cartilage. The gold standard for evaluating cartilage loss in OA is the measurement of joint space width on standard radiographs. However, in most cases the diagnosis is made well after the onset of the disease, when the symptoms are well established. Identification of early biomarkers of OA can facilitate earlier diagnosis, improve disease monitoring and predict responses to therapeutic interventions. METHODS: This study describes the bioinformatic analysis of data generated from high throughput proteomics for identification of potential biomarkers of OA. The mass spectrometry data was generated using a canine explant model of articular cartilage treated with the pro-inflammatory cytokine interleukin 1 ß (IL-1ß). The bioinformatics analysis involved the application of machine learning and network analysis to the proteomic mass spectrometry data. A rule based machine learning technique, BioHEL, was used to create a model that classified the samples into their relevant treatment groups by identifying those proteins that separated samples into their respective groups. The proteins identified were considered to be potential biomarkers. Protein networks were also generated; from these networks, proteins pivotal to the classification were identified. RESULTS: BioHEL correctly classified eighteen out of twenty-three samples, giving a classification accuracy of 78.3% for the dataset. The dataset included the four classes of control, IL-1ß, carprofen, and IL-1ß and carprofen together. This exceeded the other machine learners that were used for a comparison, on the same dataset, with the exception of another rule-based method, JRip, which performed equally well. The proteins that were most frequently used in rules generated by BioHEL were found to include a number of relevant proteins including matrix metalloproteinase 3, interleukin 8 and matrix gla protein. CONCLUSIONS: Using this protocol, combining an in vitro model of OA with bioinformatics analysis, a number of relevant extracellular matrix proteins were identified, thereby supporting the application of these bioinformatics tools for analysis of proteomic data from in vitro models of cartilage degradation.

Stratification of Companion Animal Life Stages from Electronic Medical Record Diagnosis Data.

Aging is a complex, multifactorial process, where different life stages reflect changes in metabolic processes, immune capacities, and genetic/epigenetic repertoires. With accumulating exposure to environmental stresses and deterioration of physiological functions, body systems become more prone to low-grade chronic inflammation and an increasing range of pathologies. We hypothesized that differential susceptibility to diseases across life span reflects phased changes in an organism's physiological capacity that may highlight when interventions may be appropriately used. Furthermore, the number of life stages may vary between species and be impacted by signalment such as breed. We tested this hypothesis using disease diagnoses data from veterinary electronic medical records containing almost 2 million cats and over 4 million dogs. Bi-clustering (on rates of disease diagnoses) and adaptive branch pruning were used to identify age clusters that could be used to define adult life stages. Clustering among diagnoses were then interpreted within the context of each defined life stage. The analyses identified 5 age clusters in cats and 4 age clusters within each of the 4 canine breed size categories used. This study, using population scale data for two species, one with differential size and life expectancies, is the first to our knowledge to use disease diagnosis data to define adult life stages. The life stages presented here are a result of a data-driven approach to age and disease stratification and are intended to support conversations between clinicians and clients about appropriate health care recommendations.

A consumption-based GHG inventory for the U.S. state of Oregon.

Many U.S. states conduct greenhouse gas (GHG) inventories to inform their climate change planning efforts. These inventories usually follow a production-based method adapted from the Intergovernmental Panel on Climate Change. States could also take a consumption-based perspective, however, and estimate all emissions released to support consumption in their state, regardless of where the emissions occur. In what may be the first such comprehensive inventory conducted for a U.S. state, we find that consumption-based emissions for Oregon are 47% higher than those released in-state. This finding implies that Oregon's contribution to global greenhouse gas emissions (carbon footprint) is considerably higher than traditional production-based methods would suggest. Furthermore, the consumption-based inventory helps highlight the role of goods and services (and associated purchasing behaviors) more so than do production-based methods. Accordingly, a consumption-based perspective opens new opportunities for many states and their local government partners to reduce GHG emissions, such as initiatives to advance lower-carbon public sector or household consumption, that are well within their sphere of influence. State and local governments should consider conducting consumption-based GHG inventories and adopting consumption-based emission reductions targets in order to broaden the reach and effectiveness of state and local actions in reducing global GHG emissions. Consumption-based frameworks should be viewed as a complement to, but not a substitute for, production-based (in-state) GHG emissions inventories and targets.

Botanical Extracts from Rosehip (Rosa canina), Willow Bark (Salix alba), and Nettle Leaf (Urtica dioica) Suppress IL-1ß-Induced NF-κB Activation in Canine Articular Chondrocytes.

The aim of this study was to characterize the anti-inflammatory mode of action of botanical extracts from rosehip (Rosa canina), willow bark (Salix alba), and nettle leaf (Urtica dioica) in an in vitro model of primary canine articular chondrocytes. Methods. The biological effects of the botanical extracts were studied in chondrocytes treated with IL-1ß for up to 72 h. Expression of collagen type II, cartilage-specific proteoglycan (CSPG), ß1-integrin, SOX-9, COX-2, and MMP-9 and MMP-13 was examined by western blotting. Results. The botanical extracts suppressed IL-1ß-induced NF-κB activation by inhibition of IκBα phosphorylation, IκBα degradation, p65 phosphorylation, and p65 nuclear translocation. These events correlated with downregulation of NF-κB targets including COX-2 and MMPs. The extracts also reversed the IL-1ß-induced downregulation of collagen type II, CSPG, ß1-integrin, and cartilage-specific transcription factor SOX-9 protein expression. In high-density cultures botanical extracts stimulated new cartilage formation even in the presence of IL-1ß. Conclusions. Botanical extracts exerted anti-inflammatory and anabolic effects on chondrocytes. The observed reduction of IL-1ß-induced NF-κB activation suggests that further studies are warranted to demonstrate the effectiveness of plant extracts in the treatment of OA and other conditions in which NF-κB plays pathophysiological roles.

Suitability of Dried Blood Spots for Accelerating Veterinary Biobank Collections and Identifying Metabolomics Biomarkers With Minimal Resources.

Biomarker discovery using biobank samples collected from veterinary clinics would deliver insights into the diverse population of pets and accelerate diagnostic development. The acquisition, preparation, processing, and storage of biofluid samples in sufficient volumes and at a quality suitable for later analysis with most suitable discovery methods remain challenging. Metabolomics analysis is a valuable approach to detect health/disease phenotypes. Pre-processing changes during preparation of plasma/serum samples may induce variability that may be overcome using dried blood spots (DBSs). We report a proof of principle study by metabolite fingerprinting applying UHPLC-MS of plasma and DBSs acquired from healthy adult dogs and cats (age range 1-9 years), representing each of 4 dog breeds (Labrador retriever, Beagle, Petit Basset Griffon Vendeen, and Norfolk terrier) and the British domestic shorthair cat (n = 10 per group). Blood samples (20 and 40 µL) for DBSs were loaded onto filter paper, air-dried at room temperature (3 h), and sealed and stored (4°C for ~72 h) prior to storage at -80°C. Plasma from the same blood draw (250 µL) was prepared and stored at -80°C within 1 h of sampling. Metabolite fingerprinting of the DBSs and plasma produced similar numbers of metabolite features that had similar abilities to discriminate between biological classes and correctly assign blinded samples. These provide evidence that DBSs, sampled in a manner amenable to application in in-clinic/in-field processing, are a suitable sample for biomarker discovery using UHPLC-MS metabolomics. Further, given appropriate owner consent, the volumes tested (20-40 µL) make the acquisition of remnant blood from blood samples drawn for other reasons available for biobanking and other research activities. Together, this makes possible large-scale biobanking of veterinary samples, gaining sufficient material sooner and enabling quicker identification of biomarkers of interest.

Identification of intra- and inter-individual metabolite variation in plasma metabolite profiles of cats and dogs.

The purpose of the present study was first to identify drivers of variance in plasma metabolite profiles of cats and dogs that may affect the interpretation of nutritional metabolomic studies. A total of fourteen cats and fourteen dogs housed in environmentally enriched accommodation were fed a single batch of diet to maintain body weight. Fasting blood samples were taken on days 14, 16 and 18 of the study. Gas chromatography-mass spectrometry (GC-MS), liquid chromatography (LC)-MS/MS and solid-phase extraction-LC-MS/MS analyses were used for metabolite profiling. Principal component (PC) analysis that indicated 31 and 27 % of the variance was explained in PC1 and PC2 for cats and dogs, respectively, with most individuals occupying a unique space. As the individual was a major driver of variance in the plasma metabolome, the second objective was to identify metabolites associated with the individual variation observed. The proportion of intra- and inter-individual variance was calculated for 109 cat and 101 dog metabolites with a low intra-individual variance (SD < 0.05). Of these, fifteen cat and six dog metabolites had inter-individual variance accounting for at least 90 % of the total variance. There were four metabolites common to both species (campesterol, DHA, a cholestenol and a sphingosine moiety). Many of the metabolites with >75 % inter-individual variance were common to both species and to similar areas of metabolism. In summary, the individual is an important driver of variance in the fasted plasma metabolome, and specific metabolites and areas of metabolism may be differentially regulated by individuals in two companion animal species.

Clusterin secretion is attenuated by the proinflammatory cytokines interleukin-1ß and tumor necrosis factor-α in models of cartilage degradation.

The protein clusterin has been implicated in the molecular alterations that occur in articular cartilage during osteoarthritis (OA). Clusterin exists in two isoforms with opposing functions, and their roles in cartilage have not been explored. The secreted form of clusterin (sCLU) is a cytoprotective extracellular chaperone that prevents protein aggregation, enhances cell proliferation and promotes viability, whereas nuclear clusterin acts as a pro-death signal. Therefore, these two clusterin isoforms may be putative molecular markers of repair and catabolic responses in cartilage and the ratio between them may be important. In this study, we focused on sCLU and used established, pathophysiologically relevant, in vitro models to understand its role in cytokine-stimulated cartilage degradation. The secretome of equine cartilage explants, osteochondral biopsies and isolated unpassaged chondrocytes was analyzed by western blotting for released sCLU, cartilage oligomeric protein (COMP) and matrix metalloproteinases (MMP) 3 and 13, following treatment with the proinflammatory cytokines interleukin-1ß (IL-1ß) and tumor necrosis factor-α. Release of sulfated glycosaminoglycans (sGAG) was determined using the dimethylmethylene blue assay. Clusterin messenger RNA (mRNA) expression was quantified by quantitative real-time polymerase chain reaction. MMP-3, MMP-13, COMP, and sGAG release from explants and osteochondral biopsies was elevated with cytokine treatment, confirming cartilage degradation in these models. sCLU release was attenuated with cytokine treatment in all models, potentially limiting its cytoprotective function. Clusterin mRNA expression was down-regulated 7-days post cytokine stimulation. These observations implicate sCLU in catabolic responses of chondrocytes, but further studies are required to evaluate its role in OA and its potential as an investigative biomarker.

No Observed Adverse Effects on Health Were Detected in Adult Beagle Dogs When Fed a High-Calcium Diet for 40 Weeks.

The implications of long-term high calcium (Ca) intake are well documented in growing dogs and in adult dogs of large breed size, however, the consequences on other breeds and breed sizes are yet to be determined. Eighteen neutered adult beagles, nine males and nine females aged 1.4-4.4 years, were randomized to control or test diets providing in g∙4184 kJ-1 (1000 kcal-1): 1.44 and 7.19 total Ca balanced with 1.05 and 4.25 total phosphorus, respectively, for 40 weeks. Health parameters, ultrasound scans, radiographs, glomerular filtration rate, and mineral balance were measured at eight-week intervals. All dogs remained healthy with no measured evidence of orthopedic, urinary, or renal disease. The test diet resulted in a 5.2 fold increase in fecal Ca excretion. Apparent Ca digestibility (%) and Ca balance (g/d) did not significantly (p > 0.05) change from baseline in the test diet group, although dogs displayed a positive Ca balance (maximum at week 8, 1.11 g/d with 95% CI (0.41, 1.80)) before a neutral Ca balance was restored at week 32. Despite an initial positive Ca balance, we can conclude that no measurable adverse health effects were observed as a result of the test diet fed in this study in beagles over a period of 40 weeks.

Operationally realistic validation for prediction of cocoa sensory qualities by high-throughput mass spectrometry.

The potential of analytical chemistry to predict sensory qualities of food materials is a major current theme. Standard practice is cross-validation (CV), where a set of chemical and associated sensory data is partitioned so chemometric models can be developed on training subsets, and validated on held-out subsets. CV demonstrates prediction, but is an unlikely scenario for industrial operations, where concomitant data acquisition for model development and test materials would be unwieldy. We evaluated cocoa materials of diverse provenance, and analyzed on different dates to those used in model development. Liquor extracts were analyzed by flow-injection electrospray-mass spectrometry (FIE-MS), a novel method for sensory quality prediction. FIE-MS enabled prediction of sensory qualities described by trained human panelists. Optimal models came from the Weka data-mining algorithm SimpleLinearRegression, which learns a model for the attribute giving minimal training error, which was (-)-epicatechin. This flavonoid likewise dominated partial least-squares (PLS)-regression models. Refinements of PLS (orthogonal-PLS or orthogonal signal correction) gave poorer generalization to different test sets, as did support vector machines, whose hyperparameters could not be optimized in training to avoid overfitting. In conclusion, if chemometric overfitting is avoided, chemical analysis can predict sensory qualities of food materials under operationally realistic conditions.

Metabolite fingerprinting of urine suggests breed-specific dietary metabolism differences in domestic dogs.

Selective breeding of dogs has culminated in a large number of modern breeds distinctive in terms of size, shape and behaviour. Inadvertently, a range of breed-specific genetic disorders have become fixed in some pure-bred populations. Several inherited conditions confer chronic metabolic defects that are influenced strongly by diet, but it is likely that many less obvious breed-specific differences in physiology exist. Using Labrador retrievers and miniature Schnauzers maintained in a simulated domestic setting on a controlled diet, an experimental design was validated in relation to husbandry, sampling and sample processing for metabolomics. Metabolite fingerprints were generated from 'spot' urine samples using flow injection electrospray MS (FIE-MS). With class based on breed, urine chemical fingerprints were modelled using Random Forest (a supervised data classification technique), and metabolite features (m/z) explanatory of breed-specific differences were putatively annotated using the ARMeC database (http://www.armec.org). GC-MS profiling to confirm FIE-MS predictions indicated major breed-specific differences centred on the metabolism of diet-related polyphenols. Metabolism of further diet components, including potentially prebiotic oligosaccharides, animal-derived fats and glycerol, appeared significantly different between the two breeds. Analysis of the urinary metabolome of young male dogs representative of a wider range of breeds from animals maintained under domestic conditions on unknown diets provided preliminary evidence that many breeds may indeed have distinctive metabolic differences, with significant differences particularly apparent in comparisons between large and smaller breeds.