Cannabinoid 1/2 Receptor Activation Induces Strain-Dependent Behavioral and Neurochemical Changes in Genetic Absence Epilepsy Rats From Strasbourg and Non-epileptic Control Rats

Childhood absence epilepsy (CAE) is characterized by absence seizures, which are episodes of lack of consciousness accompanied by electrographic spike-wave discharges. About 60% of children and adolescents with absence seizures are affected by major neuropsychological comorbidities, including anxiety. Endocannabinoids and monoamines are likely involved in the pathophysiology of these CAE psychiatric comorbidities. Here, we show that the synthetic cannabinoid receptor type 1/2 (CB1/2R) agonist WIN 55,212-2 (2 mg/kg) has a strain-dependent effect on anxiety-like and motor behavior when assess in the hole board test and cerebral monoaminergic levels in Genetic Absence Epilepsy Rats from Strasbourg (GAERS) and their non-epileptic control (NEC) rat strain. Using quantitative and Temporal pattern (T-pattern) analyses, we found that WIN 55,212-2 did not affect the emotional status of GAERS, but it was anxiolytic in NEC. Conversely, WIN 55,212-2 had a sedative effect in GAERS but was ineffective in NEC. Moreover, vehicle-treated GAERS more motivated to explore by implementing more complex and articulated strategies. These behavioral changes correlate with the reduction of 5-HT in the hippocampus and substantia nigra (SN) and noradrenaline (NA) in the entopeduncular nucleus (EPN) in vehicle-treated GAERS compared to NEC rats, which could contribute to their low anxiety status and hypermotility, respectively. On the other hand, the increased level of NA in the EPN and 5-HT in the SN is consistent with an activation of the basal ganglia output-mediated motor suppression observed in WIN 55,212-2-treated GAERS rats. These data support the view of a strain-dependent alteration of the endocannabinoid system in absence epilepsy by adding evidence of a lower emotional responsiveness and a basal ganglia hypersensitivity to cannabinoids in GAERS compared to NEC rats.

Vertical Organic Electrochemical Transistors and Electronics for Low Amplitude Micro-Organ Signals

Electrical signals are fundamental to key biological events such as brain activity, heartbeat, or vital hormone secretion. Their capture and analysis provide insight into cell or organ physiology and a number of bioelectronic medical devices aim to improve signal acquisition. Organic electrochemical transistors (OECT) have proven their capacity to capture neuronal and cardiac signals with high fidelity and amplification. Vertical PEDOT:PSS-based OECTs (vOECTs) further enhance signal amplification and device density but have not been characterized in biological applications. An electronic board with individually tuneable transistor biases overcomes fabrication induced heterogeneity in device metrics and allows quantitative biological experiments. Careful exploration of vOECT electric parameters defines voltage biases compatible with reliable transistor function in biological experiments and provides useful maximal transconductance values without influencing cellular signal generation or propagation. This permits successful application in monitoring micro-organs of prime importance in diabetes, the endocrine pancreatic islets, which are known for their far smaller signal amplitudes as compared to neurons or heart cells. Moreover, vOECTs capture their single-cell action potentials and multicellular slow potentials reflecting micro-organ organizations as well as their modulation by the physiological stimulator glucose. This opens the possibility to use OECTs in new biomedical fields well beyond their classical applications.

Towards the Integration of an Islet-Based Biosensor in Closed-Loop Therapies for Patients With Type 1 Diabetes

In diabetes mellitus (DM) treatment, Continuous Glucose Monitoring (CGM) linked with insulin delivery becomes the main strategy to improve therapeutic outcomes and quality of patients' lives. However, Blood Glucose (BG) regulation with CGM is still hampered by limitations of algorithms and glucose sensors. Regarding sensor technology, current electrochemical glucose sensors do not capture the full spectrum of other physiological signals, i.e., lipids, amino acids or hormones, relaying the general body status. Regarding algorithms, variability between and within patients remains the main challenge for optimal BG regulation in closed-loop therapies. This work highlights the simulation benefits to test new sensing and control paradigms which address the previous shortcomings for Type 1 Diabetes (T1D) closed-loop therapies. The UVA/Padova T1DM Simulator is the core element here, which is a computer model of the human metabolic system based on glucose-insulin dynamics in T1D patients. That simulator is approved by the US Food and Drug Administration (FDA) as an alternative for pre-clinical testing of new devices and closed-loop algorithms. To overcome the limitation of standard glucose sensors, the concept of an islet-based biosensor, which could integrate multiple physiological signals through electrical activity measurement, is assessed here in a closed-loop insulin therapy. This investigation has been addressed by an interdisciplinary consortium, from endocrinology to biology, electrophysiology, bio-electronics and control theory. In parallel to the development of an islet-based closed-loop, it also investigates the benefits of robust control theory against the natural variability within a patient population. Using 4 meal scenarios, numerous simulation campaigns were conducted. The analysis of their results then introduces a discussion on the potential benefits of an Artificial Pancreas (AP) system associating the islet-based biosensor with robust algorithms.

Dynamic Uni- and Multicellular Patterns Encode Biphasic Activity in Pancreatic Islets

Biphasic secretion is an autonomous feature of many endocrine micro-organs to fulfill physiological demands. The biphasic activity of islet β-cells maintains glucose homeostasis and is altered in type 2 diabetes. Nevertheless, underlying cellular or multicellular functional organizations are only partially understood. High-resolution noninvasive multielectrode array recordings permit simultaneous analysis of recruitment, of single-cell, and of coupling activity within entire islets in long-time experiments. Using this unbiased approach, we addressed the organizational modes of both first and second phase in mouse and human islets under physiological and pathophysiological conditions. Our data provide a new uni- and multicellular model of islet β-cell activation: during the first phase, small but highly active β-cell clusters are dominant, whereas during the second phase, electrical coupling generates large functional clusters via multicellular slow potentials to favor an economic sustained activity. Postprandial levels of glucagon-like peptide 1 favor coupling only in the second phase, whereas aging and glucotoxicity alter coupled activity in both phases. In summary, biphasic activity is encoded upstream of vesicle pools at the micro-organ level by multicellular electrical signals and their dynamic synchronization between β-cells. The profound alteration of the electrical organization of islets in pathophysiological conditions may contribute to functional deficits in type 2 diabetes.

Lorcaserin Alters Serotonin and Noradrenaline Tissue Content and Their Interaction With Dopamine in the Rat Brain

Lorcaserin is a preferential serotonin2C receptor (5-HT_2CR) agonist effective to treat obesity that has also recently been proposed to treat addiction and epilepsy. Central dopamine (DA) mechanisms are likely involved in the lorcaserin mechanism of action, but other monoamines 5-HT and noradrenaline (NA) contents or their interaction with DA might account for its effects. Here we showed that lorcaserin at 3, but not 0.3 mg/kg enhanced 5-HT content in the insular cortex, the core of the nucleus accumbens, and ventral hypothalamus. Without affecting the metabolite 5-hydroxy indole acetic acid, lorcaserin reduced the indirect index of 5-HT turnover in the hippocampus, substantia nigra, and habenula. Lorcaserin at 3 mg/kg increased NA content in the orbitofrontal cortex, the central amygdala (also at 0.3 mg/kg), the ventral hypothalamus, and the shell of the nucleus accumbens. A correlative analysis of the tissue contents between pairs of brain regions revealed that 0.3 mg/kg lorcaserin enhanced the number of correlations for 5-HT, its metabolism, and NA to a lower extent. The correlation profiles were very different between saline, 0.3 and 3 mg/kg lorcaserin. Lorcaserin enhanced the correlations established between NA or 5-HT at 0.3 and 3 mg/kg and reduced the number of correlations established between the index of the turnover for DA and 5-HT. These results show that lorcaserin modulates the biochemistry of NA and 5-HT systems in a subset of brain regions. Qualitatively, they reveal, oppositely to the DA changes, that lorcaserin at 0.3, but not 3 mg/kg, enhanced the number of correlations of 5-HT content between brain regions.

Lorcaserin bidirectionally regulates dopaminergic function site-dependently and disrupts dopamine brain area correlations in rats

Lorcaserin, which is a selective agonist of serotonin2C receptors (5-HT_2CRs), is a new FDA-approved anti-obesity drug that has also shown therapeutic promise in other brain disorders, such as addiction and epilepsy. The modulation of dopaminergic function might be critical in the therapeutic effect of lorcaserin, but its exact effect is unknown. Here, we studied the effect of the peripheral administration of lorcaserin on the ventral tegmental area (VTA), the substantia nigra pars compacta (SNc) dopaminergic neural activity, dopamine (DA) dialysis levels in the nucleus accumbens and striatum and on DA tissue levels in 29 different rat brain regions. Lorcaserin (5-640 μg/kg, i.v.) moderately inhibited only a subpopulation of VTA DA neurons, but had no effect on the SNc neurons. Lorcaserin (0.3, 3 mg/kg, i.p.) did not change VTA and SNc DA population neural activity but slightly decreased the firing rate and burst firing of the spontaneously active VTA neurons, without altering DA extracellular dialysate levels in both the nucleus accumbens and the striatum. Quantitative analysis of DA and metabolites tissue contents of the 29 areas studied revealed that lorcaserin (0.3 or 3 mg/kg, i.p.) only affected a few brain regions, i.e., increased DA in the central amygdala, ventral hypothalamus and nucleus accumbens core and decreased it in the ventromedial striatum. On the other hand, lorcaserin dramatically changed the direction and reduced the number of correlations of DA tissue content among several brain areas. These effects on DA terminal networks might be significant in the therapeutic mechanism of lorcaserin. This article is part of the special issue entitled 'Serotonin Research: Crossing Scales and Boundaries'.

Reciprocal interaction between monoaminergic systems and the pedunculopontine nucleus: Implication in the mechanism of L-DOPA

The pedunculopontine nucleus (PPN) is part of the mesencephalic locomotor region (MLR) and has been involved in the control of gait, posture, locomotion, sleep, and arousal. It likely participates in some motor and non-motor symptoms of Parkinson's disease and is regularly proposed as a surgical target to ameliorate gait, posture and sleep disorders in Parkinsonian patients. The PPN overlaps with the monoaminergic systems including dopamine, serotonin and noradrenaline in the modulation of the above-mentioned functions. All these systems are involved in Parkinson's disease and the mechanism of the anti-Parkinsonian agents, mostly L-DOPA. This suggests that PPN interacts with monoaminergic neurons and vice versa. Some evidence indicates that the PPN sends cholinergic, glutamatergic and even gabaergic inputs to mesencephalic dopaminergic cells, with the data regarding serotonergic or noradrenergic cells being less well known. Similarly, the control exerted by the PPN on dopaminergic neurons, is multiple and complex, and more extensively explored than the other monoaminergic systems. The data on the influence of monoaminergic systems on PPN neuron activity are rather scarce. While there is evidence that the PPN influences the therapeutic response of L-DOPA, it is still difficult to discerne the reciprocal action of the PPN and monoaminergic systems in this action. Additional data are required to better understand the functional organization of monoaminergic inputs to the MLR including the PPN to get a clearer picture of their interaction.

Detecting temporal changes in acoustic scenes: The variable benefit of selective attention

Four experiments investigated change detection in acoustic scenes consisting of a sum of five amplitude-modulated pure tones. As the tones were about 0.7 octave apart and were amplitude-modulated with different frequencies (in the range 2-32 Hz), they were perceived as separate streams. Listeners had to detect a change in the frequency (experiments 1 and 2) or the shape (experiments 3 and 4) of the modulation of one of the five tones, in the presence of an informative cue orienting selective attention either before the scene (pre-cue) or after it (post-cue). The changes left intensity unchanged and were not detectable in the spectral (tonotopic) domain. Performance was much better with pre-cues than with post-cues. Thus, change deafness was manifest in the absence of an appropriate focusing of attention when the change occurred, even though the streams and the changes to be detected were acoustically very simple (in contrast to the conditions used in previous demonstrations of change deafness). In one case, the results were consistent with a model based on the assumption that change detection was possible if and only if attention was endogenously focused on a single tone. However, it was also found that changes resulting in a steepening of amplitude rises were to some extent able to draw attention exogenously. Change detection was not markedly facilitated when the change produced a discontinuity in the modulation domain, contrary to what could be expected from the perspective of predictive coding.