A Systematic Search and Mapping Review of Studies on Intracerebral Microdialysis of Amino Acids, and Systematized Review of Studies on Circadian Rhythms.

BACKGROUND: Microdialysis can be used to measure amino acids in the extracellular space in vivo, based on the principle of diffusion. Variations in experimental set-up result in variations in baseline levels of the compounds measured. Variations may also be due to circadian rhythms. METHOD: We systematically searched and mapped the literature on all studies reporting baseline microdialysis measurements of histamine and the amino acids asparagine, aspartate, GABA, glutamate, glutamine, glycine, proline and taurine. We fully reviewed the studies describing circadian rhythms for histamine and the selected amino acids. RESULTS: We retrieved 2331 papers describing baseline measurements of one or more of the compounds of interest. We provide a numerical summary and lists of the publications by compound. We retrieved 11 references describing studies on the circadian rhythms of the compounds of interest. Aspartate, glutamate and histamine are generally higher during the dark than during the light phase in nocturnal rodents. For glutamine, no rhythmicity was observed. For GABA, the results were too inconsistent to generalise. For asparagine, glycine, proline and taurine, insufficient data are available. CONCLUSION: The literature on intracerebral microdialysis measurements of the amino acids is vast, but certain primary studies are still warranted. Future systematic reviews on the individual compounds can shed light on the effects of experimental variations on baseline concentrations.

A clustering algorithm for multivariate longitudinal data.

Latent growth modeling approaches, such as growth mixture models, are used to identify meaningful groups or classes of individuals in a larger heterogeneous population. But when applied to multivariate repeated measures computational problems are likely, due to the high dimension of the joint distribution of the random effects in these mixed-effects models. This article proposes a cluster algorithm for multivariate repeated data, using pseudo-likelihood and ideas based on k-means clustering, to reveal homogenous subgroups. The algorithm was demonstrated on an electro-encephalogram dataset set quantifying the effect of psychoactive compounds on the brain activity in rats.

Investigating association between behavior, corticosterone, heart rate, and blood pressure in rats using surrogate marker evaluation methodology.

The drug development process involves identifying a compound and assessing its merit through rigorous pre-clinical and clinical trials. The pre-clinical stage is designed to assess the chemical properties of the new drug, as well as to determine the steps for synthesis and purification. In this stage of drug development, circumstances might dictate the use of alternative endpoints than the originally anticipated clinically relevant endpoint. In this regard, identification and evaluation of surrogate endpoints is of paramount importance. The validation methods make it possible to quantify degrees of association between the clinically relevant endpoint, also termed the true endpoint, and the alternative, surrogate endpoint. In this paper, we adapt the surrogate marker evaluation methodology of Alonso et al. (2003); (2006), developed for the case of two longitudinal outcomes, to the situation where either a longitudinal surrogate and cross sectional true endpoint is recorded, or vice versa. The work is motivated by a preclinical experiment conducted to assess association between corticosterone (CORT), heart rate, and blood pressure in rats, the data from which are then subjected to analysis. It was found that there is a weak relationship between CORT and behavior, and between CORT on the one hand and heart rate and blood pressure on the other hand, but a reasonably high degree of association was registered between heart rate and behavior.