Genetic Variation in the Human Brain Dopamine System Influences Motor Learning and Its Modulation by L-Dopa

Dopamine is important to learning and plasticity. Dopaminergic drugs are the focus of many therapies targeting the motor system, where high inter-individual differences in response are common. The current study examined the hypothesis that genetic variation in the dopamine system is associated with significant differences in motor learning, brain plasticity, and the effects of the dopamine precursor L-Dopa. Skilled motor learning and motor cortex plasticity were assessed using a randomized, double-blind, placebo-controlled, crossover design in 50 healthy adults during two study weeks, one with placebo and one with L-Dopa. The influence of five polymorphisms with established effects on dopamine neurotransmission was summed using a gene score, with higher scores corresponding to higher dopaminergic neurotransmission. Secondary hypotheses examined each polymorphism individually. While training on placebo, higher gene scores were associated with greater motor learning (p = .03). The effect of L-Dopa on learning varied with the gene score (gene score*drug interaction, p = .008): participants with lower gene scores, and thus lower endogenous dopaminergic neurotransmission, showed the largest learning improvement with L-Dopa relative to placebo (p<.0001), while L-Dopa had a detrimental effect in participants with higher gene scores (p = .01). Motor cortex plasticity, assessed via transcranial magnetic stimulation (TMS), also showed a gene score*drug interaction (p = .02). Individually, DRD2/ANKK1 genotype was significantly associated with motor learning (p = .02) and its modulation by L-Dopa (p<.0001), but not with any TMS measures. However, none of the individual polymorphisms explained the full constellation of findings associated with the gene score. These results suggest that genetic variation in the dopamine system influences learning and its modulation by L-Dopa. A polygene score explains differences in L-Dopa effects on learning and plasticity most robustly, thus identifying distinct biological phenotypes with respect to L-Dopa effects on learning and plasticity. These findings may have clinical applications in post-stroke rehabilitation or the treatment of Parkinson''s disease.     

Scale-up strategy for bioreactors with Newtonian and non-Newtonian broths

In the scale-up of bioreactors one of the most commonly used criteria for aerobic processes is to keep the oxygen transfer coefficient constant. Nevertheless, the reproduction of the behaviour of a cell population at different scales is not dependent just on the oxygen transfer capability but rather on the oxygen transfer rate, that must be high enough to cope with the oxygen demand of the culture. In this work a strategy of scale-up is proposed based in geometric similarity, constant impeller tip speed, and constant oxygen transfer rate. The effects of the dissolved oxygen concentration, the scale-up ratio and the rheology of the broth are analysed.     

Oligodendrocytes depend on MCL-1 to prevent spontaneous apoptosis and white matter degeneration

Neurologic disorders often disproportionately affect specific brain regions, and different apoptotic mechanisms may contribute to white matter pathology in leukodystrophies or gray matter pathology in poliodystrophies. We previously showed that neural progenitors that generate cerebellar gray matter depend on the anti-apoptotic protein BCL-xL. Conditional deletion of Bcl-xL in these progenitors produces spontaneous apoptosis and cerebellar hypoplasia, while similar conditional deletion of Mcl-1 produces no phenotype. Here we show that, in contrast, postnatal oligodendrocytes depend on MCL-1. We found that brain-wide Mcl-1 deletion caused apoptosis specifically in mature oligodendrocytes while sparing astrocytes and oligodendrocyte precursors, resulting in impaired myelination and progressive white matter degeneration. Disabling apoptosis through co-deletion of Bax or Bak rescued white matter degeneration, implicating the intrinsic apoptotic pathway in Mcl-1-dependence. Bax and Bak co-deletions rescued different aspects of the Mcl-1-deleted phenotype, demonstrating their discrete roles in white matter stability. MCL-1 protein abundance was reduced in eif2b5-mutant mouse model of the leukodystrophy vanishing white matter disease (VWMD), suggesting the potential for MCL-1 deficiency to contribute to clinical neurologic disease. Our data show that oligodendrocytes require MCL-1 to suppress apoptosis, implicate MCL-1 deficiency in white matter pathology, and suggest apoptosis inhibition as a leukodystrophy therapy.Subject terms: Cell death in the nervous system, Neurodegeneration, Oligodendrocyte     

The roles of wing color pattern and geography in the evolution of Neotropical Preponini butterflies

Diversification rates and evolutionary trajectories are known to be influenced by phenotypic traits and the geographic history of the landscapes that organisms inhabit. One of the most conspicuous traits in butterflies is their wing color pattern, which has been shown to be important in speciation. The evolution of many taxa in the Neotropics has also been influenced by major geological events. Using a dated, species‐level molecular phylogenetic hypothesis for Preponini, a colorful Neotropical butterfly tribe, we evaluated whether diversification rates were constant or varied through time, and how they were influenced by color pattern evolution and biogeographical events. We found that Preponini originated approximately 28 million years ago and that diversification has increased through time consistent with major periods of Andean uplift. Even though some clades show evolutionarily rapid transitions in coloration, contrary to our expectations, these shifts were not correlated with shifts in diversification. Involvement in mimicry with other butterfly groups might explain the rapid changes in dorsal color patterns in this tribe, but such changes have not increased species diversification in this group. However, we found evidence for an influence of major Miocene and Pliocene geological events on the tribe''s evolution. Preponini apparently originated within South America, and range evolution has since been dynamic, congruent with Andean geologic activity, closure of the Panama Isthmus, and Miocene climate variability.     

Ecological features of exotic Vespula wasps (Hymenoptera: Vespidae) invading the southernmost UNESCO Biosphere Reserve

Biological Invasions - Invasive alien species may cause substantial changes and damaging impacts. Here, we document the current distribution and ecological interactions with native biota of...     

How important is it to consider lineage diversification heterogeneity in macroevolutionary studies? Lessons from the lizard family Liolaemidae

Macroevolutionary and biogeographical studies commonly apply multiple models to test state-dependent diversification. These models track the association between states of interest along a phylogeny, although many of them do not consider whether different clades might be evolving under different evolutionary drivers. Yet, they are still commonly applied to empirical studies without careful consideration of possible lineage diversification heterogeneity along the phylogenetic tree. A recent biogeographic study has suggested that orogenic uplift of the southern Andes has acted as a species pump, driving diversification of the lizard family Liolaemidae (307 described species), native to temperate southern South America. Here, we argue against the Andean uplift as main driver of evolution in this group. We show that there is a clear pattern of heterogeneous diversification in the Liolaemidae, which biases state- and environment-dependent analyses in, respectively, the GeoSSE and RPANDA programs. We show here that there are two shifts to accelerated speciation rates involving two clades that have both been classified as having “Andean” distributions. We incorporated the Geographic Hidden-State Speciation and Extinction model (GeoHiSSE) to accommodate unrelated diversification shifts, and also re-analyzed the data in RPANDA program after splitting biologically distinct clades for separate analyses, as well as including a more appropriate set of models. We demonstrate that the “Andean uplift” hypothesis is not supported when the heterogeneous diversification histories among these lizards is considered. We use the Liolaemidae as an ideal system to demonstrate potential risks of ignoring clade-specific differences in diversification patterns in macroevolutionary studies. We also implemented simulations to show that, in agreement with previous findings, the HiSSE approach can effectively and substantially reduce the level of distribution-dependent models receiving the highest AIC weights in such scenarios. However, we still find a relatively high rate (15%) of distribution-dependent models receiving the highest AIC weights, and provide recommendations related to the set of models included in the analyses that reduce these rates by half. Finally, we demonstrate that trees including clades following different dependent-drivers affect RPANDA analyses by producing different outcomes, ranging from partially correct models to completely misleading results. We provide recommendations for the implementation of both programs.     

samc: an R package for connectivity modeling with spatial absorbing Markov chains

Quantifying landscape connectivity is fundamental to better understand and predict how populations respond to environmental change. Currently, popular methods to quantify landscape connectivity emphasize how landscape features provide resistance to movement. While many tools are available to quantify landscape resistance, these do not discern between two fundamentally different sources of resistance: movement behavior and mortality. To address this issue, we developed the samc R package that quantifies landscape connectivity using absorbing Markov chain theory. Within this mathematical framework, movements are represented as transient states in the Markov chain, while mortality is represented by transitions to absorbing states. Not only does this framework explicitly account for these different issues, it provides a probabilistic approach that can incorporate both short-term and long-term dynamics, as well as species distribution and abundance. The package includes functions to quantify life expectancy, long-term visitation rates, and various spatially and temporally explicit measures of mortality and movement at the local and landscape scales. These functions in samc have been optimized to find computationally practical solutions in landscapes comprised of > 2 × 10⁶ cells. Here, we illustrate the workflow of the samc package with publicly available movement and mortality data on the endangered Florida panther Puma concolor coryi. This analysis showed that movement and mortality are generally correlated except for locations near roads (areas of high mortality risk) that are within the dispersal range of source locations. This pattern would have been undetectable with current methods that quantify movement resistance. Overall, the samc package provides a means for implementing spatial absorbing Markov chains that can distinguish between movement behavior and mortality resulting in more reliable landscape connectivity measures.