Use of information on disease diagnoses from databases for animal health economic,welfare and food safety purposes: strengths and limitations of recordings

Many animal health, welfare and food safety databases include data on clinical and test-based disease diagnoses. However, the circumstances and constraints for establishing the diagnoses vary considerably among databases. Therefore results based on different databases are difficult to compare and compilation of data in order to perform meta-analysis is almost impossible. Nevertheless, diagnostic information collected either routinely or in research projects is valuable in cross comparisons between databases, but there is a need for improved transparency and documentation of the data and the performance characteristics of tests used to establish diagnoses. The objective of this paper is to outline the circumstances and constraints for recording of disease diagnoses in different types of databases, and to discuss these in the context of disease diagnoses when using them for additional purposes, including research. Finally some limitations and recommendations for use of data and for recording of diagnostic information in the future are given. It is concluded that many research questions have such a specific objective that investigators need to collect their own data. However, there are also examples, where a minimal amount of extra information or continued validation could make sufficient improvement of secondary data to be used for other purposes. Regardless, researchers should always carefully evaluate the opportunities and constraints when they decide to use secondary data. If the data in the existing databases are not sufficiently valid, researchers may have to collect their own data, but improved recording of diagnostic data may improve the usefulness of secondary diagnostic data in the future.     

Effect of a negative energy balance induced by feed restriction in lactating sows on hepatic lipid metabolism,milk production and development of litters

In rodents, forced activation of hepatic peroxisome proliferator-activated receptor α (PPARα) by administration of exogenous PPARα activators during lactation leads to a reduction of milk triacylglycerol (TAG) production. Herein, we investigated whether a negative energy balance (NEB) induced by feed restriction (about 18% lower feed and energy intake) during lactation by increasing the release of fatty acids, which act as PPARα agonists, causes a disruption of hepatic lipid metabolism and thereby impairs milk TAG production in sows. Nutrient and energy content of the milk on day 20 of lactation and gains of litters during the first 14 d and the whole 21 d suckling period did not differ between Control and feed-restricted sows. The mRNA concentrations of several sterol regulatory element-binding protein target genes involved in lipid synthesis in the liver and the plasma concentration of TAG were reduced in the feed-restricted sows, whereas the mRNA concentrations of PPARα target genes involved in fatty acid oxidation in liver and skeletal muscle were not different between groups. In conclusion, it was shown that an NEB during lactation does not adversely affect milk composition and gains of litters, despite inhibiting hepatic expression of genes involved in lipid synthesis and reducing plasma TAG concentration. The finding that PPARα target genes involved in fatty acid utilisation in liver and muscle of sows are not induced by the NEB during lactation may explain that fatty acid availability in the mammary gland is sufficient to maintain milk TAG production and to allow normal litter gain.     

From lead to preclinical candidate: Optimization of β-homophenylalanine based inhibitors of dipeptidyl peptidase IV

A series of highly potent and selective inhibitors of DPP-4 was optimized for ADMET properties. The effort resulted in the discovery of inhibitor 1g, that exhibits excellent efficacy in an oral glucose tolerance test and an attractive pharmacokinetic profile.     

Balanced networks under spike-time dependent plasticity

The dynamics of local cortical networks are irregular, but correlated. Dynamic excitatory–inhibitory balance is a plausible mechanism that generates such irregular activity, but it remains unclear how balance is achieved and maintained in plastic neural networks. In particular, it is not fully understood how plasticity induced changes in the network affect balance, and in turn, how correlated, balanced activity impacts learning. How do the dynamics of balanced networks change under different plasticity rules? How does correlated spiking activity in recurrent networks change the evolution of weights, their eventual magnitude, and structure across the network? To address these questions, we develop a theory of spike–timing dependent plasticity in balanced networks. We show that balance can be attained and maintained under plasticity–induced weight changes. We find that correlations in the input mildly affect the evolution of synaptic weights. Under certain plasticity rules, we find an emergence of correlations between firing rates and synaptic weights. Under these rules, synaptic weights converge to a stable manifold in weight space with their final configuration dependent on the initial state of the network. Lastly, we show that our framework can also describe the dynamics of plastic balanced networks when subsets of neurons receive targeted optogenetic input.