OBJECTIVE: To investigate the effect of concentration of progesterone (P4) before artificial insemination (AI) on fertility in ovulatory or anovulatory Bos indicus cattle. DESIGN: Randomised control study METHODS: The study included 162 heifers and 96 lactating cows. On days -10 to -12, animals were examined using transrectal ultrasound, administered PG and examined for a corpus luteum (CL). Those with a CL were allocated to Experiment 1. On day 0 they were administered an intravaginal progesterone-releasing device (IVD) containing progesterone (P4) (0.78 g), oestrodiol benzoate (ODB) and either saline or PG to induce high and low circulating P4 concentrations, respectively. Those without a CL were re-examined on day 0 and those without a CL at both examinations were allocated to Experiment 2. Cows and heifers were treated with an IVD containing P4 at 0.78 g or 1.56 g to induce low or high P4 concentrations, respectively. IVDs were removed on day 7 and PG and equine chorionic gonadotrophin (eCG) were administered. Females in oestrus on day 9 were inseminated; others were administered ODB and inseminated 22-26 h later. RESULTS: Greater concentrations of circulating P4 increased the odds of pregnancy to AI in anovulatory females (P = 0.008), but decreased the odds of pregnancy in one year but not another in ovulatory animals (P × year, P = 0.019). CONCLUSION: Manipulating P4 concentrations before AI has the potential to improve pregnancy outcomes to AI in B. indicus females, but treatment may need to vary between animals classified as anovulatory or ovulatory.

Malaria infection continues to be a major health problem worldwide and drug resistance in the major human parasite species, Plasmodium falciparum, is increasing in South East Asia. Control measures including novel drugs and vaccines are in development, and contributions to the rational design and optimal usage of these interventions are urgently needed. Infection involves the complex interaction of parasite dynamics, host immunity, and drug effects. The long life cycle (48 hours in the common human species) and synchronized replication cycle of the parasite population present significant challenges to modeling the dynamics of Plasmodium infection. Coupled with these, variation in immune recognition and drug action at different life cycle stages leads to further complexity. We review the development and progress of "within-host" models of Plasmodium infection, and how these have been applied to understanding and interpreting human infection and animal models of infection.

BACKGROUND: The reference intervals (RIs) for the renal biomarkers urea and creatinine, in Greyhounds, are higher than those for non-sighthound breeds. A recent study has demonstrated a higher concentration of another biomarker of renal function, symmetric dimethylarginine (SDMA), in Greyhounds compared with other dog breeds, and thus a breed-specific RI for serum SDMA may be appropriate for Greyhounds. Greyhounds appear to be predisposed to renal disease, and the establishment of an appropriate RI for SDMA may improve the ability to identify early renal dysfunction in this breed. OBJECTIVES: The aim of this study was to establish an RI for serum SDMA in nonracing Greyhounds and to determine whether the RI for Greyhounds is different from that of non-sighthound breeds. METHODS: Blood samples were collected from 101 clinically healthy, nonracing Greyhounds for serum SDMA measurements. Results from Greyhounds were compared with serum SDMA concentrations measured in a group of non-sighthound dogs (n = 24) of similar weight, age, and sex, and with a previously established canine serum SDMA RI. RESULTS: The serum SDMA RI for Greyhounds was 6.3-19.9 μg/dL (0.31-0.99 μmol/L). Greyhounds had a significantly higher mean value (13.1 μg/dL) than that of the non-sighthound dogs (10.2 μg/dL) (P < .001), and the RI of Greyhounds was different from previously established canine RIs for SDMA. CONCLUSION: This study supports the use of a Greyhound-specific RI for SDMA. Using previously established canine RIs for this breed could result in the overdiagnosis of renal disease.

Paediatric respiratory researchers have widely adopted the multiple-breath washout (MBW) test because it allows assessment of lung function in unsedated infants and is well suited to longitudinal studies of lung development and disease. However, a substantial proportion of MBW tests in infants fail current acceptability criteria. We hypothesised that a model-based approach to analysing the data, in place of traditional simple empirical summaries, would enable more efficient use of these tests. We therefore developed a novel statistical model for infant MBW data and applied it to 1197 tests from 432 individuals from a large birth cohort study. We focus on Bayesian estimation of the lung clearance index, the most commonly used summary of lung function from MBW tests. Our results show that the model provides an excellent fit to the data and shed further light on statistical properties of the standard empirical approach. Furthermore, the modelling approach enables the lung clearance index to be estimated by using tests with different degrees of completeness, something not possible with the standard approach. Our model therefore allows previously unused data to be used rather than discarded, as well as routine use of shorter tests without significant loss of precision. Beyond our specific application, our work illustrates a number of important aspects of Bayesian modelling in practice, such as the importance of hierarchical specifications to account for repeated measurements and the value of model checking via posterior predictive distributions.

Net biome productivity (NBP) dominates the observed large variation of atmospheric CO2 annual increase over the last five decades. However, the dominant regions controlling inter-annual to multi-decadal variability of global NBP are still controversial (semi-arid regions vs. temperate or tropical forests). By developing a theory for partitioning the variance of NBP into the contributions of net primary production (NPP) and heterotrophic respiration (Rh ) at different timescales, and using both observation-based atmospheric CO2 inversion product and the outputs of 10 process-based terrestrial ecosystem models forced by 110-year observational climate, we tried to reconcile the controversy by showing that semi-arid lands dominate the variability of global NBP at inter-annual (<10 years) and tropical forests dominate at multi-decadal scales (>30 years). Results further indicate that global NBP variability is dominated by the NPP component at inter-annual timescales, and is progressively controlled by Rh with increasing timescale. Multi-decadal NBP variations of tropical rainforests are modulated by the Pacific Decadal Oscillation (PDO) through its significant influences on both temperature and precipitation. This study calls for long-term observations for the decadal or longer fluctuations in carbon fluxes to gain insights on the future evolution of global NBP, particularly in the tropical forests that dominate the decadal variability of land carbon uptake and are more effective for climate mitigation.