Phenotypic and molecular characterization of the onset of neuropathy in rodent models of diabetes mellitus

Abstract : The principal focus of this work was to study the molecular changes leading to the development of diabetic peripheral neuropathy (DPN). DPN is the most common complication associated with both type I and II diabetes mellitus (DM). This pathology is the leading cause of non-traumatic amputations. Even though the pathological and morphological changes underlying DPN are relatively well described, the implicated molecular mechanisms remain poorly understood. The following two approaches were developed to study the development of DPN in a rodent model of DM type I. As a first approach, we studied the implication of lipid metabolism in DPN phenotype, concentrating on Sterol Response Element Binding Protein (SREBP)-lc which is the key regulator of storage lipid metabolism. We showed that SREBP-1c was expressed in peripheral nerves and that its expression profile followed the expression of genes involved in storage lipid metabolism. In addition, the expression of SREBP-1c in the endoneurium of peripheral nerves was dependant upon nutritional status and this expression was also perturbed in type I diabetes. In line with this, we showed that insulin elevated the expression of SREBP-1c in primary cultured Schwann cells by activating the SREBP-1c promoter. Taken together, these findings reveal that SREBP-1c expression in Schwann cells responds to metabolic stimuli including insulin and that this response is affected in type I diabetes mellitus. This suggests that disturbed SREBP-1c regulated lipid metabolism may contribute to the pathophysiology of DPN. As a second approach, we performed a comprehensive analysis of the molecular changes associated with DPN in the Akital~1~+ mouse which is a model of spontaneous early-onset type I diabetes mellitus. This mouse expresses a mutated non-functional isoform of insulin, leading to hypoinsulinemia and hyperglycaemia. To determine the onset of DPN, weight, blood glucose and motor nerve conduction velocity (MNCV) were measured in Akital+/+ mice during the first three months of life. A decrease in MNCV was evident akeady one week after the onset of hyperglycemia. To explore the molecular changes associated with the development of DPN in these mice, we performed gene expression profiling using sciatic nerve endoneurium and dorsal root ganglia (DRG) isolated from early diabetic male Akita+/+ mice and sex-matched littermate controls. No major transcriptional changes were detected either in the DRG or in the sciatic nerve endoneurium. This experiment indicates that the phenotypic changes observed during the development of DPN are not correlated with major transcriptional alterations, but mainly with alterations at the protein level. Résumé Lors ce travail, nous nous sommes intéressés aux changements moléculaires aboutissant aux neuropathies périphériques dues au diabète (NPD). Les NPD sont la complication la plus commune du diabète de type I et de type II. Cette pathologie est une cause majeure d'amputations. Même si les changements pathologiques et morphologiques associés aux NPD sont relativement bien décrits, les mécanismes moléculaires provoquant cette pathologie sont mal connus. Deux approches ont principalement été utilisées pour étudier le développement des NPD dans des modèles murins du diabète de type I. Nous avons d'abord étudié l'impact du métabolisme des lipides sur le développement des NPD en nous concentrant sur Sterol Response Element Binding Protein (SREBP)-1 c qui est un régulateur clé des lipides de stockage. Nous avons montré que SREBP-1 c est exprimé dans les nerfs périphériques et que son profil d'expression suit celui de gènes impliqués dans le métabolisme des lipides de stockage. De plus, l'expression de SREBP-1c dans l'endoneurium des nerfs périphériques est dépendante du statut nutritionnel et est dérégulée lors de diabète de type I. Nous avons également pu montrer que l'insuline augmente l'expression de SREBP-1c dans des cultures primaires de cellules de Schwann en activant le promoteur de SREBP-1c. Ses résultats démontrent que l'expression de SREBP-1c dans les cellules de Schwann est contrôlée par des stimuli métaboliques comme l'insuline et que cette réponse est affectée dans le cas d'un diabète de type I. Ces données suggèrent que la dérégulation de l'expression de SREBP-1c lors du diabète pourrait affecter le métabolisme des lipides et ainsi contribuer à la pathophysiologie des NPD. Comme seconde approche, nous avons réalisé une analyse globale des changements moléculaires associés au développement des NPD chez les souris Akita+/+, un modèle de diabète de type I. Cette souris exprime une forme mutée et non fonctionnelle de l'insuline provoquant une hypoinsulinémie et une hyperglycémie. Afin de déterminer le début du développement de la NPD, le poids, le niveau de glucose sanguin et la vitesse de conduction nerveuse (VCN) ont été mesurés durant les 3 premiers mois de vie. Une diminution de la VCN a été détectée une semaine seulement après le développement de l'hyperglycémie. Pour explorer les changements moléculaires associés avec le développement des NPD, nous avons réalisé un profil d'expression de l'endoneurium du nerf sciatique et des ganglions spinaux isolés à partir de souris Akital+/+ et de souris contrôles Akita+/+. Aucune altération transcriptionnelle majeure n'a été détectée dans nos échantillons. Cette expérience suggère que les changements phénotypiques observés durant le développement des NPD ne sont pas corrélés avec des changements importants au niveau transcriptionnel, mais plutôt avec des altérations au niveau protéique. Résumé : Lors ce travail, nous nous sommes intéressés aux changements moléculaires aboutissant aux neuropathies périphériques dues au diabète (NPD). Les NPD sont la complication la plus commune du diabète de type I et de type II. Cette pathologie est une cause majeure d'amputations. Même si les changements pathologiques et morphologiques associés aux NPD sont relativement bien décrits, les mécanismes moléculaires provoquant cette pathologie sont mal connus. Deux approches ont principalement été utilisées pour étudier le développement des NPD dans des modèles murins du diabète de type I. Nous avons d'abord étudié l'impact du métabolisme des lipides sur le développement des NPD en nous concentrant sur Sterol Response Element Binding Protein (SREBP)-1c qui est un régulateur clé des lipides de stockage. Nous avons montré que SREBP-1 c est exprimé dans les nerfs périphériques et que son profil d'expression suit celui de gènes impliqués dans le métabolisme des lipides de stockage. De plus, l'expression de SREBP-1c dans l'endoneurium des nerfs périphériques est dépendante du statut nutritionnel et est dérégulée lors de diabète de type I. Nous avons également pu montrer que l'insuline augmente l'expression de SREBP-1c dans des cultures primaires de cellules de Schwann en activant le promoteur de SREBP-1c. Ses résultats démontrent que l'expression de SREBP-1c dans les cellules de Schwann est contrôlée par des stimuli métaboliques comme l'insuline et que cette réponse est affectée dans le cas d'un diabète de type I. Ces données suggèrent que la dérégulation de l'expression de SREBP-1c lors du diabète pourrait affecter le métabolisme des lipides et ainsi contribuer à la pathophysiologie des NPD. Comme seconde approche, nous avons réalisé une analyse globale des changements moléculaires associés au développement des NPD chez les souris Akita~~Z~+, un modèle de diabète de type I. Cette souris exprime une forme mutée et non fonctionnelle de l'insuline provoquant une hypoinsulinémie et une hyperglycémie. Afin de déterminer le début du développement de la NPD, le poids, le niveau de glucose sanguin et la vitesse de conduction nerveuse (VCN) ont été mesurés durant les 3 premiers mois de vie. Une diminution de la VCN a été détectée une semaine seulement après le développement de l'hyperglycémie. Pour explorer les changements moléculaires associés avec le développement des NPD, nous avons réalisé un profil d'expression de l'endoneurium du nerf sciatique et des ganglions spinaux isolés à partir de souris Akital+/+ et de souris contrôles Akita+/+. Aucune altération transcriptionnelle majeure n'a été détectée dans nos échantillons. Cette expérience suggère que les changements phénotypiques observés durant le développement des NPD ne sont pas corrélés avec des changements importants au niveau transcriptionnel, mais plutôt avec des altérations au niveau protéique.

Global habitat suitability models of terrestrial mammals.

Detailed large-scale information on mammal distribution has often been lacking, hindering conservation efforts. We used the information from the 2009 IUCN Red List of Threatened Species as a baseline for developing habitat suitability models for 5027 out of 5330 known terrestrial mammal species, based on their habitat relationships. We focused on the following environmental variables: land cover, elevation and hydrological features. Models were developed at 300 m resolution and limited to within species' known geographical ranges. A subset of the models was validated using points of known species occurrence. We conducted a global, fine-scale analysis of patterns of species richness. The richness of mammal species estimated by the overlap of their suitable habitat is on average one-third less than that estimated by the overlap of their geographical ranges. The highest absolute difference is found in tropical and subtropical regions in South America, Africa and Southeast Asia that are not covered by dense forest. The proportion of suitable habitat within mammal geographical ranges correlates with the IUCN Red List category to which they have been assigned, decreasing monotonically from Least Concern to Endangered. These results demonstrate the importance of fine-resolution distribution data for the development of global conservation strategies for mammals.

Using niche-based models to improve the sampling of rare species

Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.

Do stacked species distribution models reflect altitudinal diversity patterns?

The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed.

Density, climate and varying return points: an analysis of long-term population fluctuations in the threatened European tree frog.

Experimental research has identified many putative agents of amphibian decline, yet the population-level consequences of these agents remain unknown, owing to lack of information on compensatory density dependence in natural populations. Here, we investigate the relative importance of intrinsic (density-dependent) and extrinsic (climatic) factors impacting the dynamics of a tree frog (Hyla arborea) population over 22 years. A combination of log-linear density dependence and rainfall (with a 2-year time lag corresponding to development time) explain 75% of the variance in the rate of increase. Such fluctuations around a variable return point might be responsible for the seemingly erratic demography and disequilibrium dynamics of many amphibian populations.

Potential Impacts of Climate Change on Ecosystem Services in Europe: the Case of Pest Control by Vertebrates. BioScience.

Global environmental changes threaten ecosystems and cause significant alterations to the supply of ecosystem services that are vital for human well-being. We provide an assessment of the potential impacts of climate change on European diversity of vertebrates and their associated pest control services. We modeled the distributions of the species that provide this service using ensembles of forecasts from bioclimatic envelope models and then used their results to generate maps of potential species richness among vertebrate providers of pest control services. We assessed how potential richness of pest control providers would change according to different climate and greenhouse emissions scenarios. We found that potential richness of pest control providers was likely to face substantial reductions, especially in southern European countries that had economies highly dependent on agricultural yields. In much of central and northern Europe, where countries had their economies less dependent on agriculture, climate change was likely to benefit pest control providers

Towards Machine Consciousness: Grounding Abstract Models as pi-Processes

We present a two-level model of concurrent communicating systems (CCS) to serve as a basis formachine consciousness. A language implementing threads within logic programming is ¯rstintroduced. This high-level framework allows for the de¯nition of abstract processes that can beexecuted on a virtual machine. We then look for a possible grounding of these processes into thebrain. Towards this end, we map abstract de¯nitions (including logical expressions representingcompiled knowledge) into a variant of the pi-calculus. We illustrate this approach through aseries of examples extending from a purely reactive behavior to patterns of consciousness.

Three-Dimensional (3D) Microarchitecture Correlations with 2D Projection Image Gray-Level Variations Assessed by Trabecular Bone Score Using High-Resolution Computed Tomographic Acquisitions: Effects of Resolution and Noise.

The aim of the present study is to determine the level of correlation between the 3-dimensional (3D) characteristics of trabecular bone microarchitecture, as evaluated using microcomputed tomography (μCT) reconstruction, and trabecular bone score (TBS), as evaluated using 2D projection images directly derived from 3D μCT reconstruction (TBSμCT). Moreover, we have evaluated the effects of image degradation (resolution and noise) and X-ray energy of projection on these correlations. Thirty human cadaveric vertebrae were acquired on a microscanner at an isotropic resolution of 93μm. The 3D microarchitecture parameters were obtained using MicroView (GE Healthcare, Wauwatosa, MI). The 2D projections of these 3D models were generated using the Beer-Lambert law at different X-ray energies. Degradation of image resolution was simulated (from 93 to 1488μm). Relationships between 3D microarchitecture parameters and TBSμCT at different resolutions were evaluated using linear regression analysis. Significant correlations were observed between TBSμCT and 3D microarchitecture parameters, regardless of the resolution. Correlations were detected that were strongly to intermediately positive for connectivity density (0.711≤r(2)≤0.752) and trabecular number (0.584≤r(2)≤0.648) and negative for trabecular space (-0.407 ≤r(2)≤-0.491), up to a pixel size of 1023μm. In addition, TBSμCT values were strongly correlated between each other (0.77≤r(2)≤0.96). Study results show that the correlations between TBSμCT at 93μm and 3D microarchitecture parameters are weakly impacted by the degradation of image resolution and the presence of noise.

Solution scanning as a key policy tool: identifying management interventions to help maintain and enhance regulating ecosystem services

The major task of policy makers and practitioners when confronted with a resource management problem is to decide on the potential solution(s) to adopt from a range of available options. However, this process is unlikely to be successful and cost effective without access to an independently verified and comprehensive available list of options. There is currently burgeoning interest in ecosystem services and quantitative assessments of their importance and value. Recognition of the value of ecosystem services to human well-being represents an increasingly important argument for protecting and restoring the natural environment, alongside the moral and ethical justifications for conservation. As well as understanding the benefits of ecosystem services, it is also important to synthesize the practical interventions that are capable of maintaining and/or enhancing these services. Apart from pest regulation, pollination, and global climate regulation, this type of exercise has attracted relatively little attention. Through a systematic consultation exercise, we identify a candidate list of 296 possible interventions across the main regulating services of air quality regulation, climate regulation, water flow regulation, erosion regulation, water purification and waste treatment, disease regulation, pest regulation, pollination and natural hazard regulation. The range of interventions differs greatly between habitats and services depending upon the ease of manipulation and the level of research intensity. Some interventions have the potential to deliver benefits across a range of regulating services, especially those that reduce soil loss and maintain forest cover. Synthesis and applications: Solution scanning is important for questioning existing knowledge and identifying the range of options available to researchers and practitioners, as well as serving as the necessary basis for assessing cost effectiveness and guiding implementation strategies. We recommend that it become a routine part of decision making in all environmental policy areas.

Evolutionary Games in Networked Populations: Models and Experiments

Cooperation and coordination are desirable behaviors that are fundamental for the harmonious development of society. People need to rely on cooperation with other individuals in many aspects of everyday life, such as teamwork and economic exchange in anonymous markets. However, cooperation may easily fall prey to exploitation by selfish individuals who only care about short- term gain. For cooperation to evolve, specific conditions and mechanisms are required, such as kinship, direct and indirect reciprocity through repeated interactions, or external interventions such as punishment. In this dissertation we investigate the effect of the network structure of the population on the evolution of cooperation and coordination. We consider several kinds of static and dynamical network topologies, such as Baraba´si-Albert, social network models and spatial networks. We perform numerical simulations and laboratory experiments using the Prisoner's Dilemma and co- ordination games in order to contrast human behavior with theoretical results. We show by numerical simulations that even a moderate amount of random noise on the Baraba´si-Albert scale-free network links causes a significant loss of cooperation, to the point that cooperation almost vanishes altogether in the Prisoner's Dilemma when the noise rate is high enough. Moreover, when we consider fixed social-like networks we find that current models of social networks may allow cooperation to emerge and to be robust at least as much as in scale-free networks. In the framework of spatial networks, we investigate whether cooperation can evolve and be stable when agents move randomly or performing Le´vy flights in a continuous space. We also consider discrete space adopting purposeful mobility and binary birth-death process to dis- cover emergent cooperative patterns. The fundamental result is that cooperation may be enhanced when this migration is opportunistic or even when agents follow very simple heuristics. In the experimental laboratory, we investigate the issue of social coordination between indi- viduals located on networks of contacts. In contrast to simulations, we find that human players dynamics do not converge to the efficient outcome more often in a social-like network than in a random network. In another experiment, we study the behavior of people who play a pure co- ordination game in a spatial environment in which they can move around and when changing convention is costly. We find that each convention forms homogeneous clusters and is adopted by approximately half of the individuals. When we provide them with global information, i.e., the number of subjects currently adopting one of the conventions, global consensus is reached in most, but not all, cases. Our results allow us to extract the heuristics used by the participants and to build a numerical simulation model that agrees very well with the experiments. Our findings have important implications for policymakers intending to promote specific, desired behaviors in a mobile population. Furthermore, we carry out an experiment with human subjects playing the Prisoner's Dilemma game in a diluted grid where people are able to move around. In contrast to previous results on purposeful rewiring in relational networks, we find no noticeable effect of mobility in space on the level of cooperation. Clusters of cooperators form momentarily but in a few rounds they dissolve as cooperators at the boundaries stop tolerating being cheated upon. Our results highlight the difficulties that mobile agents have to establish a cooperative environment in a spatial setting without a device such as reputation or the possibility of retaliation. i.e. punishment. Finally, we test experimentally the evolution of cooperation in social networks taking into ac- count a setting where we allow people to make or break links at their will. In this work we give particular attention to whether information on an individual's actions is freely available to poten- tial partners or not. Studying the role of information is relevant as information on other people's actions is often not available for free: a recruiting firm may need to call a job candidate's refer- ences, a bank may need to find out about the credit history of a new client, etc. We find that people cooperate almost fully when information on their actions is freely available to their potential part- ners. Cooperation is less likely, however, if people have to pay about half of what they gain from cooperating with a cooperator. Cooperation declines even further if people have to pay a cost that is almost equivalent to the gain from cooperating with a cooperator. Thus, costly information on potential neighbors' actions can undermine the incentive to cooperate in dynamical networks.

Serum 25-hydroxyvitamin D level and kidney function decline in a Swiss general adult population.

Molecular evidence suggests that levels of vitamin D are associated with kidney function loss. Still, population-based studies are limited and few have considered the potential confounding effect of baseline kidney function. This study evaluated the association of serum 25-hydroxyvitamin D with change in eGFR, rapid eGFR decline, and incidence of CKD and albuminuria. Baseline (2003-2006) and 5.5-year follow-up data from a Swiss adult general population were used to evaluate the association of serum 25-hydroxyvitamin D with change in eGFR, rapid eGFR decline (annual loss >3 ml/min per 1.73 m(2)), and incidence of CKD and albuminuria. Serum 25-hydroxyvitamin D was measured at baseline using liquid chromatography-tandem mass spectrometry. eGFR and albuminuria were collected at baseline and follow-up. Multivariate linear and logistic regression models were used considering potential confounding factors. Among the 4280 people included in the analysis, the mean±SD annual eGFR change was -0.57±1.78 ml/min per 1.73 m(2), and 287 (6.7%) participants presented rapid eGFR decline. Before adjustment for baseline eGFR, baseline 25-hydroxyvitamin D level was associated with both mean annual eGFR change and risk of rapid eGFR decline, independently of baseline albuminuria. Once adjusted for baseline eGFR, associations were no longer significant. For every 10 ng/ml higher baseline 25-hydroxyvitamin D, the adjusted mean annual eGFR change was -0.005 ml/min per 1.73 m(2) (95% confidence interval, -0.063 to 0.053; P=0.87) and the risk of rapid eGFR decline was null (odds ratio, 0.93; 95% confidence interval, 0.79 to 1.08; P=0.33). Baseline 25-hydroxyvitamin D level was not associated with incidence of CKD or albuminuria. The association of 25-hydroxyvitamin D with eGFR decline is confounded by baseline eGFR. Sufficient 25-hydroxyvitamin D levels do not seem to protect from eGFR decline independently from baseline eGFR.

What can ecosystems learn? Expanding evolutionary ecology with learning theory.

BACKGROUND: The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole? RESULTS: Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, 'unsupervised learning', well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community's response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts. CONCLUSIONS: This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions. REVIEWERS: This article was reviewed by Prof. Ricard V Solé, Universitat Pompeu Fabra, Barcelona and Prof. Rob Knight, University of Colorado, Boulder.

Mother-offspring competition promotes colonization success.

Colonization is the crucial process underlying range expansions, biological invasions, and metapopulation dynamics. Which individuals leave their natal population to colonize empty habitats is a crucial question and is presently unresolved. Dispersal is the first step in colonization. However, not all dispersing individuals are necessarily good colonizers. Indeed, in some species, the phenotype of dispersers differs depending on the selective pressures that induce dispersal. In particular, kin-based interactions, a factor driving social evolution, should induce different social response profiles in nondispersing and dispersing individuals. Kin competition (defined here as between the mother and offspring) has been proven to produce dispersers with a particular phenotype that may enhance their colonizing ability. By using the common lizard (Lacerta vivipara), we conducted a multipopulation experiment to study the effect of kin competition on dispersal and colonization success. We manipulated mother-offspring interactions, which are the most important component of kin competition in the studied species, at the family and population levels and measured the consequences on colonization success. We demonstrate that mother-offspring competition at the population level significantly influences colonization success. Increased competition at the population level enhanced the colonization rate of the largest juveniles as well as the growth and survival of the colonizers. Based on these results, we calculated that kin-induced colonization halves the extinction probability of a newly initiated population. Because interactions between relatives are likely to affect the ability of a species to track habitat modifications, kin-based dispersal should be considered in the study of invasion dynamics and metapopulation functioning.

Evaluation of drug-induced neurotoxicity based on metabolomics, proteomics and electrical activity measurements in complementary CNS in vitro models.

The present study was performed in an attempt to develop an in vitro integrated testing strategy (ITS) to evaluate drug-induced neurotoxicity. A number of endpoints were analyzed using two complementary brain cell culture models and an in vitro blood-brain barrier (BBB) model after single and repeated exposure treatments with selected drugs that covered the major biological, pharmacological and neuro-toxicological responses. Furthermore, four drugs (diazepam, cyclosporine A, chlorpromazine and amiodarone) were tested more in depth as representatives of different classes of neurotoxicants, inducing toxicity through different pathways of toxicity. The developed in vitro BBB model allowed detection of toxic effects at the level of BBB and evaluation of drug transport through the barrier for predicting free brain concentrations of the studied drugs. The measurement of neuronal electrical activity was found to be a sensitive tool to predict the neuroactivity and neurotoxicity of drugs after acute exposure. The histotypic 3D re-aggregating brain cell cultures, containing all brain cell types, were found to be well suited for OMICs analyses after both acute and long term treatment. The obtained data suggest that an in vitro ITS based on the information obtained from BBB studies and combined with metabolomics, proteomics and neuronal electrical activity measurements performed in stable in vitro neuronal cell culture systems, has high potential to improve current in vitro drug-induced neurotoxicity evaluation.