A therapeutic convection-enhanced macroencapsulation device for enhancing ß cell viability and insulin secretion.

Islet transplantation for type 1 diabetes treatment has been limited by the need for lifelong immunosuppression regimens. This challenge has prompted the development of macroencapsulation devices (MEDs) to immunoprotect the transplanted islets. While promising, conventional MEDs are faced with insufficient transport of oxygen, glucose, and insulin because of the reliance on passive diffusion. Hence, these devices are constrained to two-dimensional, wafer-like geometries with limited loading capacity to maintain cells within a distance of passive diffusion. We hypothesized that convective nutrient transport could extend the loading capacity while also promoting cell viability, rapid glucose equilibration, and the physiological levels of insulin secretion. Here, we showed that convective transport improves nutrient delivery throughout the device and affords a three-dimensional capsule geometry that encapsulates 9.7-fold-more cells than conventional MEDs. Transplantation of a convection-enhanced MED (ceMED) containing insulin-secreting ß cells into immunocompetent, hyperglycemic rats demonstrated a rapid, vascular-independent, and glucose-stimulated insulin response, resulting in early amelioration of hyperglycemia, improved glucose tolerance, and reduced fibrosis. Finally, to address potential translational barriers, we outlined future steps necessary to optimize the ceMED design for long-term efficacy and clinical utility.

Application of biomaterials to advance induced pluripotent stem cell research and therapy.

Derived from any somatic cell type and possessing unlimited self-renewal and differentiation potential, induced pluripotent stem cells (iPSCs) are poised to revolutionize stem cell biology and regenerative medicine research, bringing unprecedented opportunities for treating debilitating human diseases. To overcome the limitations associated with safety, efficiency, and scalability of traditional iPSC derivation, expansion, and differentiation protocols, biomaterials have recently been considered. Beyond addressing these limitations, the integration of biomaterials with existing iPSC culture platforms could offer additional opportunities to better probe the biology and control the behavior of iPSCs or their progeny in vitro and in vivo. Herein, we discuss the impact of biomaterials on the iPSC field, from derivation to tissue regeneration and modeling. Although still exploratory, we envision the emerging combination of biomaterials and iPSCs will be critical in the successful application of iPSCs and their progeny for research and clinical translation.

Dopamine mediates the bidirectional update of interval timing.

The role of dopamine (DA) as a reward prediction error (RPE) signal in reinforcement learning (RL) tasks has been well-established over the past decades. Recent work has shown that the RPE interpretation can also account for the effects of DA on interval timing by controlling the speed of subjective time. According to this theory, the timing of the dopamine signal relative to reward delivery dictates whether subjective time speeds up or slows down: Early DA signals speed up subjective time and late signals slow it down. To test this bidirectional prediction, we reanalyzed measurements of dopaminergic neurons in the substantia nigra pars compacta of mice performing a self-timed movement task. Using the slope of ramping dopamine activity as a readout of subjective time speed, we found that trial-by-trial changes in the slope could be predicted from the timing of dopamine activity on the previous trial. This result provides a key piece of evidence supporting a unified computational theory of RL and interval timing. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Slowly evolving dopaminergic activity modulates the moment-to-moment probability of reward-related self-timed movements.

Clues from human movement disorders have long suggested that the neurotransmitter dopamine plays a role in motor control, but how the endogenous dopaminergic system influences movement is unknown. Here, we examined the relationship between dopaminergic signaling and the timing of reward-related movements in mice. Animals were trained to initiate licking after a self-timed interval following a start-timing cue; reward was delivered in response to movements initiated after a criterion time. The movement time was variable from trial-to-trial, as expected from previous studies. Surprisingly, dopaminergic signals ramped-up over seconds between the start-timing cue and the self-timed movement, with variable dynamics that predicted the movement/reward time on single trials. Steeply rising signals preceded early lick-initiation, whereas slowly rising signals preceded later initiation. Higher baseline signals also predicted earlier self-timed movements. Optogenetic activation of dopamine neurons during self-timing did not trigger immediate movements, but rather caused systematic early-shifting of movement initiation, whereas inhibition caused late-shifting, as if modulating the probability of movement. Consistent with this view, the dynamics of the endogenous dopaminergic signals quantitatively predicted the moment-by-moment probability of movement initiation on single trials. We propose that ramping dopaminergic signals, likely encoding dynamic reward expectation, can modulate the decision of when to move.

GABAA circuit mechanisms are associated with ether anesthesia-induced unconsciousness.

OBJECTIVE: An emerging paradigm for understanding how anesthetics induce altered arousal is relating receptor targeting in specific neural circuits to electroencephalogram (EEG) activity. Enhanced gamma amino-butyric acid A (GABAA) inhibitory post-synaptic currents (IPSCs) manifest with large-amplitude slow (0.1-1Hz) and frontally coherent alpha (8-12Hz) EEG oscillations during general anesthesia. Therefore, we investigated the EEG signatures of modern day derivatives of ether (MDDE) anesthesia to assess the extent to which we could obtain insights into MDDE anesthetic mechanisms. METHODS: We retrospectively studied cases from our database in which patients received isoflurane anesthesia vs. isoflurane/ketamine anesthesia (n=10 each) or desflurane anesthesia vs. desflurane/ketamine anesthesia (n=9 each). We analyzed the EEG recordings with spectral power and coherence methods. RESULTS: Similar to known GABAA circuit level mechanisms, we found that MDDE anesthesia induced large amplitude slow and frontally coherent alpha oscillations. Additionally, MDDE anesthesia also induced frontally coherent theta (4-8Hz) oscillations. Reduction of GABAergic IPSCs with ketamine resulted in beta/gamma (13-40Hz) oscillations, and significantly reduced MDDE anesthesia-induced slow, theta and alpha oscillation power. CONCLUSIONS: Large amplitude slow oscillations and coherent alpha and theta oscillations are moderated by ketamine during MDDE anesthesia. SIGNIFICANCE: These observations are consistent with the notion that GABAA circuit-level mechanisms are associated with MDDE anesthesia-induced unconsciousness.

Electroencephalogram signatures of ketamine anesthesia-induced unconsciousness.

OBJECTIVES: Ketamine is an N-methyl-d-aspartate (NMDA) receptor antagonist commonly administered as a general anesthetic. However, neural circuit mechanisms to explain ketamine anesthesia-induced unconsciousness in humans are yet to be clearly defined. Disruption of frontal-parietal network connectivity has been proposed as a mechanism to explain this brain state. However, this mechanism was recently demonstrated at subanesthetic doses of ketamine in awake-patients. Therefore, we investigated whether there is an electroencephalogram (EEG) signature specific for ketamine anesthesia-induced unconsciousness. METHODS: We retrospectively studied the EEG in 12 patients who received ketamine for the induction of general anesthesia. We analyzed the EEG dynamics using power spectral and coherence methods. RESULTS: Following the administration of a bolus dose of ketamine to induce unconsciousness, we observed a "gamma burst" EEG pattern that consisted of alternating slow-delta (0.1-4Hz) and gamma (∼27-40Hz) oscillations. This pattern was also associated with increased theta oscillations (∼4-8Hz) and decreased alpha/beta oscillations (∼10-24Hz). CONCLUSIONS: Ketamine anesthesia-induced unconsciousness is associated with a gamma burst EEG pattern. SIGNIFICANCE: The EEG signature of ketamine anesthesia-induced unconsciousness may offer new insights into NMDA circuit mechanisms for unconsciousness.