Painful events establish opponent memories: cues that precede pain are remembered negatively, whereas cues that follow pain, thus coinciding with relief are recalled positively. How do individual reinforcement-signaling neurons contribute to this "timing-dependent valence-reversal?" We addressed this question using an optogenetic approach in the fruit fly. Two types of fly dopaminergic neuron, each comprising just one paired cell, indeed established learned avoidance of odors that preceded their photostimulation during training, and learned approach to odors that followed the photostimulation. This is in striking parallel to punishment versus relief memories reinforced by a real noxious event. For only one of these neuron types, both effects were strong enough for further analyses. Notably, interfering with dopamine biosynthesis in these neurons partially impaired the punishing effect, but not the relieving after-effect of their photostimulation. We discuss how this finding constraints existing computational models of punishment versus relief memories and introduce a new model, which also incorporates findings from mammals. Furthermore, whether using dopaminergic neuron photostimulation or a real noxious event, more prolonged punishment led to stronger relief. This parametric feature of relief may also apply to other animals and may explain particular aspects of related behavioral dysfunction in humans.

BackgroundExcessive alcohol intake is associated with adverse immune response-related effects, however, acute and chronic abuse differently modulate monocyte activation. In this study, we have evaluated the phenotypic and functional changes of monocytes in acutely intoxicated healthy volunteers (HV).MethodsTwenty-two HV consumed individually adjusted amounts of alcoholic beverages until reaching a blood alcohol level of 1‰ after 4h (T4). Peripheral blood was withdrawn before and 2h (T2), 4h (T4), 6h (T6), 24h (T24), and 48h (T48) after starting the experiment and stained for CD14, CD16 and TLR4. CD14brightCD16-, CD14brightCD16+ and CD14dimCD16+ monocyte subsets and their TLR4 expression were analyzed by flow cytometry. Inflammasome activation via caspase-1 in CD14+ monocytes was measured upon an ex vivo in vitro LPS stimulation. Systemic IL-1β and adhesion capacity of isolated CD14+ monocytes upon LPS stimulation were evaluated.ResultsThe percentage of CD14+ monocyte did not change following alcohol intoxication, whereas CD14brightCD16- monocyte subset significantly increased at T2 and T24, CD14brightCD16+ at T2, T4 and T6 and CD14dimCD16+ at T4 and T6. The relative fraction of TLR4 expressing CD14+ monocytes as well as the density of TLR4 surface presentation increased at T2 and decreased at T48 significantly. TLR4+CD14+ monocytes were significantly enhanced in all subsets at T2. TLR4 expression significantly decreased in CD14brightCD16- at T48, in CD14brightCD16+ at T24 and T48, increased in CD14dimCD16+ at T2. IL-1β release upon LPS stimulation decreased at T48, correlating with TLR4 receptor expression. Alcohol downregulated inflammasome activation following ex vivo in vitro stimulation with LPS between T2 and T48 vs. T0. The adhesion capacity of CD14+ monocytes decreased from T2 with significance at T4, T6 and T48. Following LPS administration, a significant reduction of adhesion was observed at T4 and T6.ConclusionsAlcohol intoxication immediately redistributes monocyte subsets toward the pro-inflammatory phenotype with their subsequent differentiation into the anti-inflammatory phenotype. This is paralleled by a significant functional depression, suggesting an alcohol-induced time-dependent hyporesponsiveness of monocytes to pathogenic triggers.

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IntroductionGiven its wide availability and cost-effectiveness, multidimensional flow cytometry (mFC) became a core method in the field of immunology allowing for the analysis of a broad range of individual cells providing insights into cell subset composition, cellular behavior, and cell-to-cell interactions. Formerly, the analysis of mFC data solely relied on manual gating strategies. With the advent of novel computational approaches, (semi-)automated gating strategies and analysis tools complemented manual approaches.MethodsUsing Bayesian network analysis, we developed a mathematical model for the dependencies of different obtained mFC markers. The algorithm creates a Bayesian network that is a HC tree when including raw, ungated mFC data of a randomly selected healthy control cohort (HC). The HC tree is used to classify whether the observed marker distribution (either patients with amyotrophic lateral sclerosis (ALS) or HC) is predicted. The relative number of cells where the probability q is equal to zero is calculated reflecting the similarity in the marker distribution between a randomly chosen mFC file (ALS or HC) and the HC tree.ResultsIncluding peripheral blood mFC data from 68 ALS and 35 HC, the algorithm could correctly identify 64/68 ALS cases. Tuning of parameters revealed that the combination of 7 markers, 200 bins, and 20 patients achieved the highest AUC on a significance level of p < 0.0001. The markers CD4 and CD38 showed the highest zero probability. We successfully validated our approach by including a second, independent ALS and HC cohort (55 ALS and 30 HC). In this case, all ALS were correctly identified and side scatter and CD20 yielded the highest zero probability. Finally, both datasets were analyzed by the commercially available algorithm ‘Citrus’, which indicated superior ability of Bayesian network analysis when including raw, ungated mFC data.DiscussionBayesian network analysis might present a novel approach for classifying mFC data, which does not rely on reduction techniques, thus, allowing to retain information on the entire dataset. Future studies will have to assess the performance when discriminating clinically relevant differential diagnoses to evaluate the complementary diagnostic benefit of Bayesian network analysis to the clinical routine workup.

Tobacco smoking is strongly linked to vascular damage contributing to the development of hypertension, atherosclerosis, as well as an increased risk for neurodegeneration. Still, the contribution of the innate immune system to the development of vascular damage upon chronic tobacco use before the onset of clinical symptoms is not fully elucidated. Notably, our data provide evidence that a single acute exposure to tobacco in never smokers elicits a secretion of extracellular vesicles by endothelial cells expressing CD105 and CD49e, granting further recognition of early preclinical biomarker of vascular damage. Further, we investigated the effects of smoking on the immune system of healthy asymptomatic chronic smokers compared to never-smokers and focused on the innate immune system. Our data reveal a distinct immune landscape representative for early stages of vascular damage before tobacco smoking related disease develop in clinically asymptomatic chronic smokers. These results indicate a dysregulated immuno-vascular axis in chronic tobacco smokers that are considered healthy individuals. The distinct alterations are characterized by increased CD36 expression by blood monocyte subsets, neutrophilia, increased plasma IL-18 and reduced levels of IL-33, IL-10 and IL-8. Further, the detection of lower circulating BDNF and elevated sTREM2, specific markers for neurodegeneration, suggests a considerable pre-clinical impact of tobacco smoking on CNS function in clinically healthy individuals. These findings provide further insight into the initial and ongoing effects of tobacco smoking and the potential vascular damage contributing to the progression of neurodegenerative disorders, specifically cerebrovascular dysfunction and dementia.