Comprehensive analysis of frequency and phenotype of T regulatory cells in HIV infection: CD39 expression of FoxP3+ T regulatory cells correlates with progressive disease

There are conflicting data about the frequency and role of regulatory T cells (Tregs) during the course of HIV infection. Peripheral blood of a large cohort of HIV-infected patients (n = 131) at different stages of disease, including 15 long-term nonprogressors and 21 elite controllers, was analyzed to determine the frequency and phenotype of Tregs, defined as CD4(+), CD25(high), CD127(low), FoxP3(high) cells. A significantly increased relative frequency of Tregs within the CD4(+) compartment of HIV(+) patients compared to that of healthy controls (P < 0.0001) was observed. Additionally, the relative frequency of Tregs directly correlated with HIV viral load and inversely with CD4(+) counts. However, the absolute Treg number was reduced in HIV-infected patients versus healthy controls (P < 0.0001), with the exception of elite controllers (P > 0.05). The loss of absolute Treg numbers coincided with rising markers of immune activation (P < 0.0006). The initiation of antiviral therapy significantly increased absolute Treg numbers (P < 0.0031). We find that the expression of CD39, a newly defined ectonucleotidase with immunomodulatory functions on Tregs, correlated with progressive HIV disease, HIV viral load, and immune activation. Of note, when tested in peripheral blood mononuclear cells of healthy volunteers, the in vitro capacity to suppress T-cell proliferation was limited to CD4(+), CD25(high), CD39(+) T cells. Interestingly, Tregs of elite controllers exhibited not only the highest expression of CCR5, CTLA-4, and ICOS but also the lowest level of CD39. The data presented here reconcile the seemingly contradictory results of previous studies looking at Tregs in HIV and highlight the complexity of Treg-mediated immunoregulation during human viral infections.     

Desensitization of nicotinic acetylcholine receptors in central nervous system neurons of the stick insect (Carausius morosus) by imidacloprid and sulfoximine insecticides

Imidacloprid, sulfoxaflor and two experimental sulfoximine insecticides caused generally depressive symptoms in stick insects, characterized by stillness and weakness, while also variably inducing postural changes such as persistent ovipositor opening, leg flexion or extension and abdomen bending that could indicate excitation of certain neural circuits. We examined the same compounds on nicotinic acetylcholine receptors in stick insect neurons, which have previously been shown to desensitize in the presence of ACh. Brief U-tube application of 10⁻⁴ M solutions of insecticides for 1 s evoked currents that were much smaller than ACh-evoked currents, and depressed subsequent ACh-evoked currents for several minutes, indicating that the compounds are low-efficacy partial agonists that potently desensitize the receptors. Much lower concentrations of insecticides applied in the bath for longer periods did not activate currents, but inhibited ACh-evoked currents via desensitization of the receptors. Previously described fast- and slowly-desensitizing nACh currents, I_ACh1 and I_ACh2 respectively, were each found to consist of two components with differing sensitivities to the insecticides. Imidacloprid applied in the bath desensitized high-sensitivity components, I_ACh1H and I_ACh2H with IC₅₀s of 0.18 and 0.13 pM, respectively. It desensitized the low-sensitivity slowly desensitizing component, I_ACh2L, with an IC₅₀ of 2.6 nM, while a component of the fast-desensitizing current, I_ACh1L, was least sensitive, with an IC₅₀ of 81 nM I_ACh1L appeared to be insensitive to the three sulfoximines tested, whereas all three sulfoximines potently desensitized I_ACh1H and both slowly desensitizing components, with IC₅₀s between 2 and 7 nM. We conclude that selective desensitization of certain nAChR subtypes can account for the insecticidal actions of imidacloprid and sulfoximines in stick insects.     

From neuron to behavior: dynamic equation-based prediction of biological processes in motor control

This article presents the use of continuous dynamic models in the form of differential equations to describe and predict temporal changes in biological processes and discusses several of its important advantages over discontinuous bistable ones, exemplified on the stick insect walking system. In this system, coordinated locomotion is produced by concerted joint dynamics and interactions on different dynamical scales, which is therefore difficult to understand. Modeling using differential equations possesses, in general, the potential for the inclusion of biological detail, the suitability for simulation, and most importantly, parameter manipulation to make predictions about the system behavior. We will show in this review article how, in case of the stick insect walking system, continuous dynamical system models can help to understand coordinated locomotion.     

Deriving neural network controllers from neuro-biological data: implementation of a single-leg stick insect controller

This article presents modular recurrent neural network controllers for single legs of a biomimetic six-legged robot equipped with standard DC motors. Following arguments of Ekeberg et?al. (Arthropod Struct Dev 33:287?C300, 2004), completely decentralized and sensori-driven neuro-controllers were derived from neuro-biological data of stick-insects. Parameters of the controllers were either hand-tuned or optimized by an evolutionary algorithm. Employing identical controller structures, qualitatively similar behaviors were achieved for robot and for stick insect simulations. For a wide range of perturbing conditions, as for instance changing ground height or up- and downhill walking, swing as well as stance control were shown to be robust. Behavioral adaptations, like varying locomotion speeds, could be achieved by changes in neural parameters as well as by a mechanical coupling to the environment. To a large extent the simulated walking behavior matched biological data. For example, this was the case for body support force profiles and swing trajectories under varying ground heights. The results suggest that the single-leg controllers are suitable as modules for hexapod controllers, and they might therefore bridge morphological- and behavioral-based approaches to stick insect locomotion control.     

Dominance of local sensory signals over inter-segmental effects in a motor system: experiments

Legged locomotion requires that information local to one leg, and inter-segmental signals coming from the other legs are processed appropriately to establish a coordinated walking pattern. However, very little is known about the relative importance of local and inter-segmental signals when they converge upon the central pattern generators (CPGs) of different leg joints. We investigated this question on the CPG of the middle leg coxa?Ctrochanter (CTr)-joint of the stick insect which is responsible for lifting and lowering the leg. We used a semi-intact preparation with an intact front leg stepping on a treadmill, and simultaneously stimulated load sensors of the middle leg. We found that middle leg load signals induce bursts in the middle leg depressor motoneurons (MNs). The same local load signals could also elicit rhythmic activity in the CPG of the middle leg CTr-joint when the stimulation of middle leg load sensors coincided with front leg stepping. However, the influence of front leg stepping was generally weak such that front leg stepping alone was only rarely accompanied by switching between middle leg levator and depressor MN activity. We therefore conclude that the impact of the local sensory signals on the levator?Cdepressor motor system is stronger than the inter-segmental influence through front leg stepping.     

Using individual-muscle specific instead of across-muscle mean data halves muscle simulation error

Hill-type parameter values measured in experiments on single muscles show large across-muscle variation. Using individual-muscle specific values instead of the more standard approach of across-muscle means might therefore improve muscle model performance. We show here that using mean values increased simulation normalized RMS error in all tested motor nerve stimulation paradigms in both isotonic and isometric conditions, doubling mean simulation error from 9 to 18 (different at p?<?0.0001). These data suggest muscle-specific measurement of Hill-type model parameters is necessary in work requiring highly accurate muscle model construction. Maximum muscle force (F _max) showed large (fourfold) across-muscle variation. To test the role of F _max in model performance we compared the errors of models using mean F _max and muscle-specific values for the other model parameters, and models using muscle-specific F _max values and mean values for the other model parameters. Using muscle-specific F _max values did not improve model performance compared to using mean values for all parameters, but using muscle-specific values for all parameters but F _max did (to an error of 14, different from muscle-specific, mean all parameters, and mean only F _max errors at p?≤ 0.014). Significantly improving model performance thus required muscle-specific values for at least a subset of parameters other than F _max, and best performance required muscle-specific values for this subset and F _max. Detailed consideration of model performance suggested that remaining model error likely stemmed from activation of both fast and slow motor neurons in our experiments and inadequate specification of model activation dynamics.