The neuronal monocarboxylate transporter MCT2: its regulation by BDNF and its role in learning and memory

Glucose has been considered the major, if not the exclusive, energy substrate for the brain. But under certain physiological and pathological conditions other substrates, namely monocarboxylates (lactate, pyruvate and ketone bodies), can contribute significantly to satisfy brain energy demands. These monocarboxylates need to be transported across the blood-brain barrier or out of astrocytes into the extracellular space and taken up into neurons. It has been shown that monocarboxylates are transported by a family of proton-linked transporters called monocarboxylate transporters (MCTs). In the central nervous system, MCT2 is the predominant neuronal isoform and little is known about the regulation of its expression. Noradrenaline (NA), insulin and IGF-1 were previously shown to enhance the expression of MCT2 in cultured cortical neurons via a translational mechanism. Here we demonstrate that the well known brain neurotrophic factor BDNF enhances MCT2 protein expression in cultured cortical neurons and in synaptoneurosome preparations in a time- and concentrationdependent manner without affecting MCT2 mRNA levels. We observed that BDNF induced MCT2 expression by activation of MAPK as well as PI3K/Akt/mTOR signaling pathways. Furthermore, we investigated the possible post-transcriptional regulation of MCT2 expression by a neuronal miRNA. Then, we demonstrated that BDNF enhanced MCT2 expression in the hippocampus in vivo, in parallel with some post-synaptic proteins such as PSD95 and AMPA receptor GluR2/3 subunits, and two immediate early genes Arc and Zif268 known to be expressed in conditions related to synaptic plasticity. In the last part, we demonstrated in vivo that a downregulation of hippocampal MCT2 via silencing with an appropriate lentiviral vector in mice caused an impairment of working memory without reference memory deficit. In conclusion, these results suggest that regulation of neuronal monocarboxylate transporter MCT2 expression could be a key event in the context of synaptic plasticity, allowing an adequate energy substrate supply in situations of altered synaptic efficacy. - Le glucose représente le substrat énergétique majeur pour le cerveau. Cependant, dans certaines conditions physiologiques ou pathologiques, le cerveau a la capacité d'utiliser des substrats énergéiques appartenant à la classe des monocarboxylates (lactate, pyruvate et corps cétoniques) afin de satisfaire ses besoins énergétiques. Ces monocarboxylates doivent être transportés à travers la barrière hématoencéphalique mais aussi hors des astrocytes vers l'espace extracellulaire puis re-captés par les neurones. Leur transport est assuré par une famillle de transporteurs aux monocarboxylates (MCTs). Dans le système nerveux central, les neurones expriment principalement l'isoforme MCT2 mais peu d'informations sont disponibles concernant la régulation de son expression. Il a été montré que la noradrénaline, l'insuline et l'IGF-1 induisent l'expression de MCT2 dans des cultures de neurones corticaux par un mécanisme traductionnel. Dans cette étude nous démontrons dans un premier temps que le facteur neurotrophique BDNF augmente l'expression de MCT2 à la fois dans des cultures de neurones corticaux et dans les préparations synaptoneurosomales selon un décours temporel et une gamme de concentrations propre. Aucun changement n'a été observé concernant les niveaux d'ARNm de MCT2. Nous avons observé que le BDNF induisait l'expression de MCT2 par l'activation simultanée des voies de signalisation MAPK et PI3K/Akt/mTOR. De plus, nous nous sommes intéressés à une potentielle régulation par les micro-ARNs de la synthèse de MCT2. Ensuite, nous avons démontré que le BDNF induit aussi l'expression de MCT2 dans l'hippocampe de la souris en parallèle avec d'autres protéines post-synaptiques telles que PSD95 et GluR2/3 et avec deux « immediate early genes » tels que Arc et Zif268 connus pour être exprimés dans des conditions de plasticité synaptique. Dans un dernier temps, nous avons démontré qu'une diminution d'expression de MCT2 induite par le biais d'un siRNA exprimé via un vecteur lentiviral dans l'hippocampe de souris générait des déficits de mémoire de travail sans affecter la mémoire de référence. En conclusion, ces résultats nous suggèrent que le transporteur aux monocarboxylates neuronal MCT2 serait essentiel pour l'apport énergétique du lactate pour les neurones dans des conditions de haute activité neuronale comme c'est le cas pendant les processus de plasticité synaptique.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

Evolutionarily stable learning schedules and cumulative culture in discrete generation models.

Individual learning (e.g., trial-and-error) and social learning (e.g., imitation) are alternative ways of acquiring and expressing the appropriate phenotype in an environment. The optimal choice between using individual learning and/or social learning may be dictated by the life-stage or age of an organism. Of special interest is a learning schedule in which social learning precedes individual learning, because such a schedule is apparently a necessary condition for cumulative culture. Assuming two obligatory learning stages per discrete generation, we obtain the evolutionarily stable learning schedules for the three situations where the environment is constant, fluctuates between generations, or fluctuates within generations. During each learning stage, we assume that an organism may target the optimal phenotype in the current environment by individual learning, and/or the mature phenotype of the previous generation by oblique social learning. In the absence of exogenous costs to learning, the evolutionarily stable learning schedules are predicted to be either pure social learning followed by pure individual learning ("bang-bang" control) or pure individual learning at both stages ("flat" control). Moreover, we find for each situation that the evolutionarily stable learning schedule is also the one that optimizes the learned phenotype at equilibrium.

Apprendre ensemble pourtravailler ensemble: l'education interprofessionnelle, un mythe ou une réalité [Learning together to work together: interprofessional education, a myth or reality?].

This article offers a review of the literature on interprofessional education (EIP), a form of education which brings together members of two or more professions in a joint training. In this course, participants gain knowledge through other professionals and about them. The goal of EIP is to improve collaboration between health professionals and the quality of patient care. The EIP is booming worldwide and seems for from a mere fad. This expansion can be explained by several factors: the increasing importance attributed to the quality of care and patient safety, care changes (aging population and increasing chronic diseases) and the shortage of health professionals. The expectations of the EIP are large, while the evidence supporting its effectiveness is being built.

Machine learning for spatial environmental data. Theory, applications and software

The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.

The Learning Affect Monitor (LAM) - A computer-based system integrating quantitative and qualitative assessment of affective states in daily life.

The Learning Affect Monitor (LAM) is a new computer-based assessment system integrating basic dimensional evaluation and discrete description of affective states in daily life, based on an autonomous adapting system. Subjects evaluate their affective states according to a tridimensional space (valence and activation circumplex as well as global intensity) and then qualify it using up to 30 adjective descriptors chosen from a list. The system gradually adapts to the user, enabling the affect descriptors it presents to be increasingly relevant. An initial study with 51 subjects, using a 1 week time-sampling with 8 to 10 randomized signals per day, produced n = 2,813 records with good reliability measures (e.g., response rate of 88.8%, mean split-half reliability of .86), user acceptance, and usability. Multilevel analyses show circadian and hebdomadal patterns, and significant individual and situational variance components of the basic dimension evaluations. Validity analyses indicate sound assignment of qualitative affect descriptors in the bidimensional semantic space according to the circumplex model of basic affect dimensions. The LAM assessment module can be implemented on different platforms (palm, desk, mobile phone) and provides very rapid and meaningful data collection, preserving complex and interindividually comparable information in the domain of emotion and well-being.

Learning about Bayesian networks for forensic interpretation : An example based on the "the problem of multiple propositions"

Both, Bayesian networks and probabilistic evaluation are gaining more and more widespread use within many professional branches, including forensic science. Notwithstanding, they constitute subtle topics with definitional details that require careful study. While many sophisticated developments of probabilistic approaches to evaluation of forensic findings may readily be found in published literature, there remains a gap with respect to writings that focus on foundational aspects and on how these may be acquired by interested scientists new to these topics. This paper takes this as a starting point to report on the learning about Bayesian networks for likelihood ratio based, probabilistic inference procedures in a class of master students in forensic science. The presentation uses an example that relies on a casework scenario drawn from published literature, involving a questioned signature. A complicating aspect of that case study - proposed to students in a teaching scenario - is due to the need of considering multiple competing propositions, which is an outset that may not readily be approached within a likelihood ratio based framework without drawing attention to some additional technical details. Using generic Bayesian networks fragments from existing literature on the topic, course participants were able to track the probabilistic underpinnings of the proposed scenario correctly both in terms of likelihood ratios and of posterior probabilities. In addition, further study of the example by students allowed them to derive an alternative Bayesian network structure with a computational output that is equivalent to existing probabilistic solutions. This practical experience underlines the potential of Bayesian networks to support and clarify foundational principles of probabilistic procedures for forensic evaluation.

The handaxe and the microscope: individual and social learning in a multidimensional model of adaptation

When individuals learn by trial-and-error, they perform randomly chosen actions and then reinforce those actions that led to a high payoff. However, individuals do not always have to physically perform an action in order to evaluate its consequences. Rather, they may be able to mentally simulate actions and their consequences without actually performing them. Such fictitious learners can select actions with high payoffs without making long chains of trial-and-error learning. Here, we analyze the evolution of an n-dimensional cultural trait (or artifact) by learning, in a payoff landscape with a single optimum. We derive the stochastic learning dynamics of the distance to the optimum in trait space when choice between alternative artifacts follows the standard logit choice rule. We show that for both trial-and-error and fictitious learners, the learning dynamics stabilize at an approximate distance of root n/(2 lambda(e)) away from the optimum, where lambda(e) is an effective learning performance parameter depending on the learning rule under scrutiny. Individual learners are thus unlikely to reach the optimum when traits are complex (n large), and so face a barrier to further improvement of the artifact. We show, however, that this barrier can be significantly reduced in a large population of learners performing payoff-biased social learning, in which case lambda(e) becomes proportional to population size. Overall, our results illustrate the effects of errors in learning, levels of cognition, and population size for the evolution of complex cultural traits. (C) 2013 Elsevier Inc. All rights reserved.

Mice with chronic GSH deficit display phenotypical anomalies that resemble key aspects of schizophrenia

ABSTRACTSchizophrenia is a major psychiatric disorder occurring with a prevalence of 1% in the worldwide population. It develops progressively with psychosis onset in late adolescence or earlyadulthood. The disorder can take many different facets and has a highly diffuse anddistributed neuropathology including deficits in major neurotransmitter systems,myelination, stress regulation, and metabolism. The delayed onset and the heterogeneouspathology suggest that schizophrenia is a developmental disease that arises from interplayof genetic and environmental factors during sensitive periods. Redox dysregulation due to animbalance between pro-oxidants and antioxidant defence mechanisms is among the riskfactors for schizophrenia. Glutathione (GSH) is the major cellular redox regulator andantioxidant. Levels of GSH are decreased in cerebrospinal fluid, prefrontal cortex and postmortemstriatum of schizophrenia patients. Moreover, polymorphisms of the key GSHsynthesizingenzyme, glutamate-cysteine ligase, modifier (GCLM) subunit, are associatedwith the disease, suggesting that GSH deficit is of genetic origin. Here we used miceknockout (KO) for the GCLM gene, which display chronic GSH deficit (~70 to 80% decrease)to investigate the direct link between redox dysregulation and schizophrenia. Accordingly,we evaluated whether GCLM KO compared to normal wildtype mice display behavioralchanges that relate to schizophrenia symptoms and whether their brains showmorphological, functional or metabolic alterations that resemble those in patients.Moreover, we exposed pubertal GCLM mice to repeated mild stress and measured theirhormonal and behavioral stress reactivity. Our data show that chronic GSH deficit isassociated with altered emotion- and stress-related behaviors, deficient prepulse inhibition,pronounced amphetamine-induced hyperlocomotion but normal spatial learning andworking memory. These changes represent important schizophrenia endophenotypes.Moreover, this particular pattern of change indicates impairment of the ventralhippocampus (VH) and related circuitry as opposed to the dorsal hippocampus (DH), which isimplicated in spatial information processing. This is consistent with a selective deficit ofparvalbumin positive interneurons and gamma oscillation in the VH but not DH. Increasedlevels of circulating stress hormones in KO mice following pubertal stress corroborate VHdysfunction as it is involved in negative feedback control of the stress response. VHstructural and functional deficits are frequently found in the schizophrenic brain. Metabolicevaluation of the developing GCLM KO anterior cortex using in vivo magnetic resonancespectroscopy revealed elevated glutamine (Gln), glutamate (Glu), Gln/Glu and N-acetylaspartate(NAA) during the pre-pubertal period. Similar changes are reported in earlyschizophrenia. Overall, we observe phenotypic anomalies in GSH deficient GCLM KO micethat correspond to major schizophrenia endophenotypes. This supports an important rolefor redox dysregulation in schizophrenia and validates the GCLM KO mouse as model for thedisease. Moreover, our results indicate that puberty may be a sensitive period for redoxsensitivechanges highliting the importance of early intervention. Gln, Gln/Glu, Glu and NAAmay qualify as early metabolic biomarkers to identify young at-risk individuals. Since chronictreatment with NAC normalized most metabolic changes in GCLM KO mice, NAC may be oneadjunct treatment of choice for early intervention in patients.RESUMELa schizophrénie est une maladie psychiatrique majeure avec une prévalence de 1% dans lapopulation. Son développement est progressif, les premières psychoses apparaissant àl'adolescence ou au début de l'âge adulte. La maladie a plusieurs présentations et uneneuropathologie étendue, qui inclut des déficits neurochimiques, métaboliques, de lamyélination et de la régulation du stress. L'émergence tardive et l'hétérogénéité de lapathologie suggèrent que la schizophrénie est une maladie développementale, favorisée pardes facteurs génétiques et environnementaux durant des périodes sensibles. La dérégulationrédox, due à un déséquilibre entre facteurs pro-oxidantes et défenses anti-oxidantes,constitue un facteur de risque. Le glutathion (GSH) est le principal régulateur rédox et antioxidantdes cellules, ses taux sont diminués dans le liquide céphalorachidien, le cortexpréfrontal et le striatum de patients. De plus, des variations du gène codant la sous-unitémodulatrice (GCLM) de la glutamate-cystéine ligase, enzyme de synthèse du GSH, sontassociés la maladie, suggérant que le déficit observé chez les patients est d'originegénétique. Nous avons donc utilisé des souris ayant une délétion du gène GCLM (KO), quiont un déficit chronique en GSH (70-80%), afin d'étudier le lien entre une dérégulation rédoxet la schizophrénie. Nous avons évalué si ces souris présentent des altérationscomportementales analogues aux symptômes de la maladie, et des modificationsstructurelles, fonctionnelles et métaboliques au niveau du cerveau, ressemblant à celles despatients. De plus, nous avons soumis les souris à des stresses modérés durant la puberté,puis mesuré les réponses hormonales et comportementales. Les animaux présentent undéficit pré-attentionnel du traitement des informations moto-sensorielles, un déficit pourcertains apprentissages, une réponse accrue à l'amphétamine, mais leurs mémoires spatialeet de travail sont préservées. Ces atteintes comportementales sont analogues à certainsendophénotypes de la schizophrénie. De plus, ces changements comportementaux sontlargement expliqués par une perturbation morphologique et fonctionnelle de l'hippocampeventral (HV). Ainsi, nous avons observé un déficit sélectif des interneurones immunoréactifsà la parvalbumine et une désynchronisation neuronale dans l'HV. L'hippocampe dorsal,impliqué dans l'orientation spatiale, demeure en revanche intact. L'augmentationd'hormones de stress dans le sang des souris KO suite à un stress prépubertal soutien aussil'hypothèse d'une dysfonction de l'HV, connu pour moduler ce type de réponse. Des déficitsstructurels et fonctionnels dans l'hippocampe antérieur (ventral) ont d'ailleurs été rapportéschez des patients schizophrènes. Par de résonance magnétique, nous avons également suivile profil métabolique du le cortex antérieur au cours du développement postnatal des sourisKO. Ces mesures ont révélé des taux élevés de glutamine (Gln), glutamate (Glu), du ratioGln/Glu, et de N-acétyl-aspartate (NAA) durant la période prépubertale. Des altérationssimilaires sont décrites chez les patients durant la phase précoce. Nous avons donc révélédes anomalies phénotypiques chez les souris GCLM KO qui reflètent certainsendophénotypes de la schizophrénie. Nos résultats appuient donc le rôle d'une dérégulationrédox dans l'émergence de la maladie et le potentiel des souris KO comme modèle. De plus,cette étude met en évidence la puberté comme période particulièrement sensible à unedérégulation rédox, renforçant l'importance d'une intervention thérapeutique précoce. Dansce cadre, Gln, Gln/Glu, Glu and NAA seraient des biomarqueurs clés pour identifier de jeunesindividus à risque. De part son efficacité dans notre modèle, NAC pourrait être unesubstance de choix dans le traitement précoce des patients.

Quantitative genetics of learning ability and resistance to stress in Drosophila melanogaster.

Even though laboratory evolution experiments have demonstrated genetic variation for learning ability, we know little about the underlying genetic architecture and genetic relationships with other ecologically relevant traits. With a full diallel cross among twelve inbred lines of Drosophila melanogaster originating from a natural population (0.75 < F < 0.93), we investigated the genetic architecture of olfactory learning ability and compared it to that for another behavioral trait (unconditional preference for odors), as well as three traits quantifying the ability to deal with environmental challenges: egg-to-adult survival and developmental rate on a low-quality food, and resistance to a bacterial pathogen. Substantial additive genetic variation was detected for each trait, highlighting their potential to evolve. Genetic effects contributed more than nongenetic parental effects to variation in traits measured at the adult stage: learning, odorant perception, and resistance to infection. In contrast, the two traits quantifying larval tolerance to low-quality food were more strongly affected by parental effects. We found no evidence for genetic correlations between traits, suggesting that these traits could evolve at least to some degree independently of one another. Finally, inbreeding adversely affected all traits.

Prevalence and dimensions of sexual orientation in Swiss adolescents: a cross-sectional survey of 16 to 20-year-old students.

AIM: Sexual orientation plays an important part in building identity during adolescence. The aim of this study was to describe patterns of sexual orientation, including sexual attraction, fantasies, affiliations and behaviour. METHODS: The study was based on the analysis of data from computerized self-administered questionnaires of a Swiss national survey on the sexual life of 16 to 20-year-old adolescents (n = 2,075 girls and 2,208 boys.). RESULTS: Overall, 95.0% of girls and 96.2% of boys described themselves as predominantly heterosexual; 1.4% of girls and 1.7% of boys as predominantly homosexual or bisexual; and 2.8% of teenagers (girls: 3.6%; boys: 2.1%) were "unsure" of their sexual orientation. The reported prevalence of homosexual attraction (girls: 2.0%; boys: 2.9%) exceeded homosexual fantasies (girls: 0.4%; boys: 0.5%) and affiliations (girls: 0.3%; boys: 0.5%). Among the 4205 respondents, 31 girls (1.5% of girls) and 56 boys (2.5% of boys) reported sexual behaviour (experience or penetrative intercourse) with a person of the same sex. Among 1.5% of girls and 2.5% of boys who reported sexual behaviour with a person of the same sex, 65% of boys and 80% of girls nevertheless considered themselves as heterosexual. CONCLUSION: For a comprehensive understanding of sexual orientation in adolescence a differentiated look at dimensions of sexual orientation is indispensable. This applies to clinical settings, public health and research.