Lidocaine effects on acetylcholine-elicited currents from mouse superior cervical ganglion neurons

Lidocaine is a commonly used local anaesthetic that, besides blocking voltage-dependent Na+ channels, has multiple inhibitory effects on muscle-type nicotinic acetylcholine (ACh) receptors (nAChRs). In the present study, we have investigated the effects of lidocaine on ACh-elicited currents (IAChs) from cultured mouse superior cervical ganglion (SCG) neurons, which mainly express heteromeric α3β4 nAChRs. Neurons were voltage-clamped by using the perforated-patch method and IAChs were elicited by fast application of ACh (100-300 μM), either alone or in presence of lidocaine at different concentrations. IAChs were reversibly blocked by lidocaine in a concentration-dependent way (IC50 = 41 μM; nH close to 1) and the inhibition was, at least partially, voltage-dependent, indicating an open-channel blockade. Besides, lidocaine blocked resting (closed) nAChRs, as evidenced by the increased inhibition caused by a 12 s lidocaine application just before its co-application with the agonist, and also enhanced IAChs desensitisation, at concentrations close to the IC50. These results indicate that lidocaine has diverse inhibitory actions on neuronal heteromeric nAChRs resembling those previously reported for Torpedo (muscle-type) nAChRs ( Alberola-Die et al., 2011). The similarity of lidocaine actions on different subtypes of heteromeric nAChRs differs with the specific effects of other compounds, restricted to particular subtypes of nAChRs.

Muscle-Type Nicotinic Receptor Blockade by Diethylamine, the Hydrophilic Moiety of Lidocaine

Lidocaine bears in its structure both an aromatic ring and a terminal amine, which can be protonated at physiological pH, linked by an amide group. Since lidocaine causes multiple inhibitory actions on nicotinic acetylcholine receptors (nAChRs), this work was aimed to determine the inhibitory effects of diethylamine (DEA), a small molecule resembling the hydrophilic moiety of lidocaine, on Torpedo marmorata nAChRs microtransplanted to Xenopus oocytes. Similarly to lidocaine, DEA reversibly blocked acetylcholine-elicited currents (IACh) in a dose-dependent manner (IC50 close to 70 μM), but unlike lidocaine, DEA did not affect IACh desensitization. IACh inhibition by DEA was more pronounced at negative potentials, suggesting an open-channel blockade of nAChRs, although roughly 30% inhibition persisted at positive potentials, indicating additional binding sites outside the pore. DEA block of nAChRs in the resting state (closed channel) was confirmed by the enhanced IACh inhibition when pre-applying DEA before its co-application with ACh, as compared with solely DEA and ACh co-application. Virtual docking assays provide a plausible explanation to the experimental observations in terms of the involvement of different sets of drug binding sites. So, at the nAChR transmembrane (TM) domain, DEA and lidocaine shared binding sites within the channel pore, giving support to their open-channel blockade; besides, lidocaine, but not DEA, interacted with residues at cavities among the M1, M2, M3, and M4 segments of each subunit and also at intersubunit crevices. At the extracellular (EC) domain, DEA and lidocaine binding sites were broadly distributed, which aids to explain the closed channel blockade observed. Interestingly, some DEA clusters were located at the α-γ interphase of the EC domain, in a cavity near the orthosteric binding site pocket; by contrast, lidocaine contacted with all α-subunit loops conforming the ACh binding site, both in α-γ and α-δ and interphases, likely because of its larger size. Together, these results indicate that DEA mimics some, but not all, inhibitory actions of lidocaine on nAChRs and that even this small polar molecule acts by different mechanisms on this receptor. The presented results contribute to a better understanding of the structural determinants of nAChR modulation.

Disipation Functions of Flow Equations in Models of Complex Systems

In an open system, each disequilibrium causes a force. Each force causes a flow process, these being represented by a flow variable formally written as an equation called flow equation, and if each flow tends to equilibrate the system, these equations mathematically represent the tendency to that equilibrium. In this paper, the authors, based on the concepts of forces and conjugated fluxes and dissipation function developed by Onsager and Prigogine, they expose the following hypothesis: Is replaced in Prigogine’s Theorem the flow by its equation or by a flow orbital considering conjugate force as a gradient. This allows to obtain a dissipation function for each flow equation and a function of orbital dissipation.

Comparison among monitoring strategies to assess water flow dynamic and soil hydraulic properties in agricultural soils

Irrigated agriculture is usually performed in semi-arid regions despite scarcity of water resources. Therefore, optimal irrigation management by monitoring the soil is essential, and assessing soil hydraulic properties and water flow dynamics is presented as a first measure. For this purpose, the control of volumetric water content, θ, and pressure head, h, is required. This study adopted two types of monitoring strategies in the same experimental plot to control θ and h in the vadose zone: i) non-automatic and more time-consuming; ii) automatic connected to a datalogger. Water flux was modelled with Hydrus-1D using the data collected from both acquisition strategies independently (3820 daily values for the automatic; less than 1000 for the non-automatic). Goodness-of-fit results reported a better adjustment in case of automatic sensors. Both model outputs adequately predicted the general trend of θ and h, but with slight differences in computed annual drainage (711 mm and 774 mm). Soil hydraulic properties were inversely estimated from both data acquisition systems. Major differences were obtained in the saturated volumetric water content, θs, and the n and α van Genuchten model shape parameters. Saturated hydraulic conductivity, Ks, shown lower variability with a coefficient of variation range from 0.13 to 0.24 for the soil layers defined. Soil hydraulic properties were better assessed through automatic data acquisition as data variability was lower and accuracy was higher.