Intraluminal Behavior of Various Transporter Substrates in the Rat Gastrointestinal Tract.

PURPOSE: The aim of this study was to evaluate the intraluminal behavior of various transporter substrates in different regions of the gastrointestinal (GI) tract. METHODS: Drug solutions containing non-absorbable FITC-dextran 4000 (FD-4), were orally administered to rats. Residual water was sampled from the GI regions to measure the luminal drug concentration. RESULTS: Cephalexin (CEX), a substrate of the proton-coupled oligopeptide transporter, was absorbed rapidly, and no drug was detected in the lower small intestine. Saquinavir (SQV) was primarily absorbed in the upper region. However, unlike CEX, SQV was detected even in the lower segment probably due to the efflux of SQV via P-glycoprotein (P-gp). The concentration of methotrexate (MTX) showed a similar pattern to that of non-absorbable FD-4. The low absorption of MTX was probably due to efflux via several efflux transporters, and the limited expression of proton-coupled folate transporter, an absorptive transporter for MTX, in the upper region. CONCLUSION: This study revealed that the luminal concentration pattern of each drug differed considerably depending on the site because of the different absorption properties and luminal volumes. Although further investigation using a specific transporter inhibitor or transporter-knockout animals are necessary to clarify the actual contribution of each transporter to the drug absorption, this information will be valuable in evaluating transporter-mediated drug absorption in in vitro transport studies for ensuring optimal drug concentrations.

Extending the integrate-and-fire model to account for metabolic dependencies.

It is widely accepted that the brain, like any other physical system, is subjected to physical constraints that restrict its operation. The brain's metabolic demands are particularly critical for proper neuronal function, but the impact of these constraints continues to remain poorly understood. Detailed single-neuron models are recently integrating metabolic constraints, but these models' computational resources make it challenging to explore the dynamics of extended neural networks, which are governed by such constraints. Thus, there is a need for a simplified neuron model that incorporates metabolic activity and allows us to explore the dynamics of neural networks. This work introduces an energy-dependent leaky integrate-and-fire (EDLIF) neuronal model extension to account for the effects of metabolic constraints on the single-neuron behavior. This simple, energy-dependent model could describe the relationship between the average firing rate and the Adenosine triphosphate (ATP) cost as well as replicate a neuron's behavior under a clinical setting such as amyotrophic lateral sclerosis (ALS). Additionally, EDLIF model showed better performance in predicting real spike trains - in the sense of spike coincidence measure - than the classical leaky integrate-and-fire (LIF) model. The simplicity of the energy-dependent model presented here makes it computationally efficient and, thus, suitable for studying the dynamics of large neural networks.

Off-line effects of alpha-frequency transcranial alternating current stimulation on a visuomotor learning task.

INTRODUCTION: It has been suggested that transcranial alternating current stimulation (tACS) at both alpha and beta frequencies promotes motor function as well as motor learning. However, limited information exists on the aftereffects of tACS on motor learning and neurophysiological profiles such as entrainment and neural plasticity in parallel. Therefore, in the present study, we examined the effect of tACS on motor learning and neurophysiological profiles using an off-line tACS condition. METHODS: Thirty-three healthy participants were randomly assigned to 10 Hz, 20 Hz, or the sham group. Participants performed visuomotor learning tasks consisting of a baseline task (preadaptation task) and training task (adaptation task) to reach a target with a lever-type controller. Electroencephalography was recorded from eight locations during the learning tasks. tACS was performed between the preadaptation task and adaptation task over the left primary motor cortex for 10 min at 1 mA. RESULTS: As a result, 10 Hz tACS was shown to be effective for initial angular error correction in the visuomotor learning tasks. However, there were no significant differences in neural oscillatory activities among the three groups. CONCLUSION: These results suggest that initial motor learning can be facilitated even when 10 Hz tACS is applied under off-line conditions. However, neurophysiological aftereffects were recently demonstrated to be induced by tACS at individual alpha frequencies rather than fixed alpha tACS, which suggests that the neurophysiological aftereffects by fixed frequency stimulation in the present study may have been insufficient to generate changes in oscillatory neural activity.