Background

Hematologic and biochemical reference intervals depend on many factors, including age. A review of the literature highlights the lack of reference intervals for 6-wk-old specific pathogen free (SPF) Hampshire-Yorkshire crossbred pigs. For translational research, 6-wk-old pigs represent an important animal model for both human juvenile colitis and diabetes mellitus type 2 given the similarities between the porcine and human gastrointestinal maturation process. The aim of this study was to determine reference intervals for hematological and biochemical parameters in healthy 6-wk-old crossbred pigs. Blood samples were collected from 66 clinically healthy Hampshire-Yorkshire pigs. The pigs were 6 wks old, represented both sexes, and were housed in a SPF facility. Automated hematological and biochemical analysis were performed using an ADVIA 120 Hematology System and a Cobas 6000 C501 Clinical Chemistry Analyzer.

Results

Reference intervals were calculated using both parametric and nonparametric methods. The mean, median, minimum, and maximum values were calculated.

Conclusion

As pigs are used more frequently as medical models of human disease, having reference intervals for commonly measured hematological and biochemical parameters in 6-wk-old pigs will be useful. The reference intervals calculated in this study will aid in the diagnosis and monitoring of both naturally occurring and experimentally induced disease. In comparison to published reference intervals for older non SPF pigs, notable differences in leukocyte populations, and in levels of sodium, potassium, glucose, protein, and alkaline phosphatase were observed.

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.

Cyanobacteria have the potential to produce bulk and fine chemicals and members belonging to Nostoc sp. have received particular attention due to their relatively fast growth rate and the relative ease with which they can be harvested. Nostoc punctiforme is an aerobic, motile, Gram-negative, filamentous cyanobacterium that has been studied intensively to enhance our understanding of microbial carbon and nitrogen fixation. The genome of the type strain N. punctiforme ATCC 29133 was sequenced in 2001 and the scientific community has used these genome data extensively since then. Advances in bioinformatics tools for sequence annotation and the importance of this organism prompted us to resequence and reanalyze its genome and to make both, the initial and improved annotation, available to the scientific community. The new draft genome has a total size of 9.1 Mbp and consists of 65 contiguous pieces of DNA with a GC content of 41.38% and 7664 protein-coding genes. Furthermore, the resequenced genome is slightly (5152 bp) larger and contains 987 more genes with functional prediction when compared to the previously published version. We deposited the annotation of both genomes in the Department of Energy's IMG database to facilitate easy genome exploration by the scientific community without the need of in-depth bioinformatics skills. We expect that an facilitated access and ability to search the N. punctiforme ATCC 29133 for genes of interest will significantly facilitate metabolic engineering and genome prospecting efforts and ultimately the synthesis of biofuels and natural products from this keystone organism and closely related cyanobacteria.