57 resultados para Patch-Clamp


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Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).

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This paper describes a computational and statistical study of the influence of morphological changes on the electrophysiological response of neurons from an animal model of Alzheimer's Disease (AD). We combined experimental morphological data from rat hippocampal CA1 pyramidal cells with a well-established model of active membrane properties. Dendritic morphology and the somatic response to simulated current clamp conditions were then compared for cells from the control and the AD group. The computational approach allowed us to single out the influences of neuromorphology on neuronal response by eliminating the effects of active channel variability. The results did not reveal a simple relationship between morphological changes associated with AD and changes in neural response. However, they did suggest the existence of more complex than anticipated relationships between dendritic morphology and single-cell electrophysiology.

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Background: The effects of landscape modifications on the long-term persistence of wild animal populations is of crucial importance to wildlife managers and conservation biologists, but obtaining experimental evidence using real landscapes is usually impossible. To circumvent this problem we used individual-based models (IBMs) of interacting animals in experimental modifications of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of four species with contrasting life-history characteristics: skylark (Alauda arvensis), vole (Microtus agrestis), a ground beetle (Bembidion lampros) and a linyphiid spider (Erigone atra). This allows us to quantify the population implications of experimental modifications of landscape configuration and composition. Methodology/Principal Findings: Starting with a real agricultural landscape, we progressively reduced landscape complexity by (i) homogenizing habitat patch shapes, (ii) randomizing the locations of the patches, and (iii) randomizing the size of the patches. The first two steps increased landscape fragmentation. We assessed the effects of these manipulations on the long-term persistence of animal populations by measuring equilibrium population sizes and time to recovery after disturbance. Patch rearrangement and the presence of corridors had a large effect on the population dynamics of species whose local success depends on the surrounding terrain. Landscape modifications that reduced population sizes increased recovery times in the short-dispersing species, making small populations vulnerable to increasing disturbance. The species that were most strongly affected by large disturbances fluctuated little in population sizes in years when no perturbations took place. Significance: Traditional approaches to the management and conservation of populations use either classical methods of population analysis, which fail to adequately account for the spatial configurations of landscapes, or landscape ecology, which accounts for landscape structure but has difficulty predicting the dynamics of populations living in them. Here we show how realistic and replicable individual-based models can bridge the gap between non-spatial population theory and non-dynamic landscape ecology. A major strength of the approach is its ability to identify population vulnerabilities not detected by standard population viability analyses.

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Levetiracetam (LEV) is a prominent antiepileptic drug (AED) which binds to neuronal synaptic vesicle glycoprotein 2A (SV2A) protein and has reported effects on ion channels, but retains a poorly-defined mechanism of action. Here, we investigate inhibition of voltage-dependent Ca2+ (CaV) channels as a potential mechanism by which LEV imparts effects on neuronal activity. We used electrophysiological methods to investigate the effects of LEV on cholinergic synaptic transmission and CaV channel activity in superior cervical ganglion neurons (SCGNs). In parallel, we investigated effects of the LEV ‘inactive’ R-enantiomer, UCB L060. Thus, LEV, but not UCB L060 (each 100 μM), inhibited synaptic transmission between SCGNs in long-term culture in a time-dependent manner, significantly reducing excitatory postsynaptic potentials (EPSP) following ≥30 min application. In isolated SCGNs, LEV pretreatment (≥1 h), but not acute (5 min) application, significantly inhibited whole-cell IBa amplitude. In current clamp recordings, LEV reduced the amplitude of the afterhyperpolarizing potential (AHP) in a Ca2+-dependent manner, but also increased action potential (AP) latency in a Ca2+-independent manner, suggesting further mechanisms associated with reduced excitability. Intracellular LEV application (4-5 min) caused a rapid inhibition of IBa amplitude to an extent comparable to that seen following extracellular LEV pretreatment ( ≥ 1 h). Neither pretreatment nor intracellular application of UCB L060 produced any inhibitory effects on IBa amplitude. These results identify a stereospecific intracellular pathway by which LEV inhibits presynaptic CaV channels; resultant reductions in neuronal excitability are proposed to contribute to the anticonvulsant effects of LEV.

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The formulation and implementation of LEAF-2, the Land Ecosystem–Atmosphere Feedback model, which comprises the representation of land–surface processes in the Regional Atmospheric Modeling System (RAMS), is described. LEAF-2 is a prognostic model for the temperature and water content of soil, snow cover, vegetation, and canopy air, and includes turbulent and radiative exchanges between these components and with the atmosphere. Subdivision of a RAMS surface grid cell into multiple areas of distinct land-use types is allowed, with each subgrid area, or patch, containing its own LEAF-2 model, and each patch interacts with the overlying atmospheric column with a weight proportional to its fractional area in the grid cell. A description is also given of TOPMODEL, a land hydrology model that represents surface and subsurface downslope lateral transport of groundwater. Details of the incorporation of a modified form of TOPMODEL into LEAF-2 are presented. Sensitivity tests of the coupled system are presented that demonstrate the potential importance of the patch representation and of lateral water transport in idealized model simulations. Independent studies that have applied LEAF-2 and verified its performance against observational data are cited. Linkage of RAMS and TOPMODEL through LEAF-2 creates a modeling system that can be used to explore the coupled atmosphere–biophysical–hydrologic response to altered climate forcing at local watershed and regional basin scales.

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Voltage-gated potassium (Kv) channels are essential components of neuronal excitability. The Kv3.4 channel protein is widely distributed throughout the central nervous system (CNS), where it can form heteromeric or homomeric Kv3 channels. Electrophysiological studies reported here highlight a functional role for this channel protein within neurons of the dorsal vagal nucleus (DVN). Current clamp experiments revealed that blood depressing substance (BDS) and intracellular dialysis of an anti-Kv3.4 antibody prolonged the action potential duration. In addition, a BDS sensitive, voltage-dependent, slowly inactivating outward current was observed in voltage clamp recordings from DVN neurons. Electrical stimulation of the solitary tract evoked EPSPs and IPSPs in DVN neurons and BDS increased the average amplitude and decreased the paired pulse ratio, consistent with a presynaptic site of action. This presynaptic modulation was action potential dependent as revealed by ongoing synaptic activity. Given the role of the Kv3 proteins in shaping neuronal excitability, these data highlight a role for homomeric Kv3.4 channels in spike timing and neurotransmitter release in low frequency firing neurons of the DVN.

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The voltage-gated potassium channel subunit Kv3.1 confers fast firing characteristics to neurones. Kv3.1b subunit immunoreactivity (Kv3.1b-IR) was widespread throughout the medulla oblongata, with labelled neurones in the gracile, cuneate and spinal trigeminal nuclei. In the nucleus of the solitary tract (NTS), Kv3.1b-IR neurones were predominantly located close to the tractus solitarius (TS) and could be GABAergic or glutamatergic. Ultrastructurally, Kv3.1b-IR was detected in NTS terminals, some of which were vagal afferents. Whole-cell current-clamp recordings from neurones near the TS revealed electrophysiological characteristics consistent with the presence of Kv3.1b subunits: short duration action potentials (4.2 +/- 1.4 ms) and high firing frequencies (68.9 +/- 5.3 Hz), both sensitive to application of TEA (0.5 mm) and 4-aminopyridine (4-AP; 30 mum). Intracellular dialysis of an anti-Kv3.1b antibody mimicked and occluded the effects of TEA and 4-AP in NTS and dorsal column nuclei neurones, but not in dorsal vagal nucleus or cerebellar Purkinje cells (which express other Kv3 subunits, but not Kv3.1b). Voltage-clamp recordings from outside-out patches from NTS neurones revealed an outward K(+) current with the basic characteristics of that carried by Kv3 channels. In NTS neurones, electrical stimulation of the TS evoked EPSPs and IPSPs, and TEA and 4-AP increased the average amplitude and decreased the paired pulse ratio, consistent with a presynaptic site of action. Synaptic inputs evoked by stimulation of a region lacking Kv3.1b-IR neurones were not affected, correlating the presence of Kv3.1b in the TS with the pharmacological effects.

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Land-use changes can alter the spatial population structure of plant species, which may in turn affect the attractiveness of flower aggregations to different groups of pollinators at different spatial scales. To assess how pollinators respond to spatial heterogeneity of plant distributions and whether honeybees affect visitation by other pollinators we used an extensive data set comprising ten plant species and their flower visitors from five European countries. In particular we tested the hypothesis that the composition of the flower visitor community in terms of visitation frequencies by different pollinator groups were affected by the spatial plant population structure, viz. area and density measures, at a within-population (‘patch’) and among-population (‘population’) scale. We found that patch area and population density were the spatial variables that best explained the variation in visitation frequencies within the pollinator community. Honeybees had higher visitation frequencies in larger patches, while bumblebees and hoverflies had higher visitation frequencies in sparser populations. Solitary bees had higher visitation frequencies in sparser populations and smaller patches. We also tested the hypothesis that honeybees affect the composition of the pollinator community by altering the visitation frequencies of other groups of pollinators. There was a positive relationship between visitation frequencies of honeybees and bumblebees, while the relationship with hoverflies and solitary bees varied (positive, negative and no relationship) depending on the plant species under study. The overall conclusion is that the spatial structure of plant populations affects different groups of pollinators in contrasting ways at both the local (‘patch’) and the larger (‘population’) scales and, that honeybees affect the flower visitation by other pollinator groups in various ways, depending on the plant species under study. These contrasting responses emphasize the need to investigate the entire pollinator community when the effects of landscape change on plant–pollinator interactions are studied.

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Firing of action potentials in excitable cells accelerates ATP turnover. The voltage-gated potassium channel Kv2.1 regulates action potential frequency in central neurons, whereas the ubiquitous cellular energy sensor AMP-activated protein kinase (AMPK) is activated by ATP depletion and protects cells by switching off energy-consuming processes. We show that treatment of HEK293 cells expressing Kv2.1 with the AMPK activator A-769662 caused hyperpolarizing shifts in the current-voltage relationship for channel activation and inactivation. We identified two sites (S440 and S537) directly phosphorylated on Kv2.1 by AMPK and, using phosphospecific antibodies and quantitative mass spectrometry, show that phosphorylation of both sites increased in A-769662-treated cells. Effects of A-769662 were abolished in cells expressing Kv2.1 with S440A but not with S537A substitutions, suggesting that phosphorylation of S440 was responsible for these effects. Identical shifts in voltage gating were observed after introducing into cells, via the patch pipette, recombinant AMPK rendered active but phosphatase-resistant by thiophosphorylation. Ionomycin caused changes in Kv2.1 gating very similar to those caused by A-769662 but acted via a different mechanism involving Kv2.1 dephosphorylation. In cultured rat hippocampal neurons, A-769662 caused hyperpolarizing shifts in voltage gating similar to those in HEK293 cells, effects that were abolished by intracellular dialysis with Kv2.1 antibodies. When active thiophosphorylated AMPK was introduced into cultured neurons via the patch pipette, a progressive, time-dependent decrease in the frequency of evoked action potentials was observed. Our results suggest that activation of AMPK in neurons during conditions of metabolic stress exerts a protective role by reducing neuronal excitability and thus conserving energy.

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Spontaneous activity of the brain at rest frequently has been considered a mere backdrop to the salient activity evoked by external stimuli or tasks. However, the resting state of the brain consumes most of its energy budget, which suggests a far more important role. An intriguing hint comes from experimental observations of spontaneous activity patterns, which closely resemble those evoked by visual stimulation with oriented gratings, except that cortex appeared to cycle between different orientation maps. Moreover, patterns similar to those evoked by the behaviorally most relevant horizontal and vertical orientations occurred more often than those corresponding to oblique angles. We hypothesize that this kind of spontaneous activity develops at least to some degree autonomously, providing a dynamical reservoir of cortical states, which are then associated with visual stimuli through learning. To test this hypothesis, we use a biologically inspired neural mass model to simulate a patch of cat visual cortex. Spontaneous transitions between orientation states were induced by modest modifications of the neural connectivity, establishing a stable heteroclinic channel. Significantly, the experimentally observed greater frequency of states representing the behaviorally important horizontal and vertical orientations emerged spontaneously from these simulations. We then applied bar-shaped inputs to the model cortex and used Hebbian learning rules to modify the corresponding synaptic strengths. After unsupervised learning, different bar inputs reliably and exclusively evoked their associated orientation state; whereas in the absence of input, the model cortex resumed its spontaneous cycling. We conclude that the experimentally observed similarities between spontaneous and evoked activity in visual cortex can be explained as the outcome of a learning process that associates external stimuli with a preexisting reservoir of autonomous neural activity states. Our findings hence demonstrate how cortical connectivity can link the maintenance of spontaneous activity in the brain mechanistically to its core cognitive functions.

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Bees provide essential pollination services that are potentially affected both by local farm management and the surrounding landscape. To better understand these different factors, we modelled the relative effects of landscape composition (nesting and floral resources within foraging distances), landscape configuration (patch shape, interpatch connectivity and habitat aggregation) and farm management (organic vs. conventional and local-scale field diversity), and their interactions, on wild bee abundance and richness for 39 crop systems globally. Bee abundance and richness were higher in diversified and organic fields and in landscapes comprising more high-quality habitats; bee richness on conventional fields with low diversity benefited most from high-quality surrounding land cover. Landscape configuration effects were weak. Bee responses varied slightly by biome. Our synthesis reveals that pollinator persistence will depend on both the maintenance of high-quality habitats around farms and on local management practices that may offset impacts of intensive monoculture agriculture.

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Numerous studies have shown that attention is biased toward threatening events. More recent evidence has also found attentional biases for stimuli that are relevant to the current and temporary goals of an individual. We examined whether goal-relevant information still evokes an attentional bias when this information competes with threatening events. In three experiments, participants performed a dot probe task combined with a separate task that induced a temporary goal. The results of Experiment 1 showed that attention was oriented to goal-relevant pictures in the dot probe task when these pictures were simultaneously presented with neutral or threatening pictures. Whether goal-relevant pictures themselves were threatening or neutral did not influence the results. Experiment 2 replicated these findings in a sample of highly trait-anxious participants. Experiment 3 showed that attention was automatically deployed to stimuli relevant to a temporary goal even in the presence of stimuli that signal imminent and genuine threat (i.e., a colored patch signaling the presentation of an aversive noise). These findings further corroborate the conclusion that an individual's current and temporary goals guide early attentional processes

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Agonists of protease-activated receptor 2 (PAR(2)) evoke hyperexcitability of dorsal root ganglia (DRG) neurons by unknown mechanisms. We examined the cellular mechanisms underlying PAR(2)-evoked hyperexcitability of mouse colonic DRG neurons to determine their potential role in pain syndromes such as visceral hyperalgesia. Colonic DRG neurons were identified by injecting Fast Blue and DiI retrograde tracers into the mouse colon. Using immunofluorescence, we found that DiI-labelled neurons contained PAR(2) immunoreactivity, confirming the presence of receptors on colonic neurons. Whole-cell current-clamp recordings of acutely dissociated neurons demonstrated that PAR(2) activation with a brief application (3 min) of PAR(2) agonists, SLIGRL-NH(2) and trypsin, evoked sustained depolarizations (up to 60 min) which were associated with increased input resistance and a marked reduction in rheobase (50% at 30 min). In voltage clamp, SLIGRL-NH(2) markedly suppressed delayed rectifier I(K) currents (55% at 10 min), but had no effect on the transient I(A) current or TTX-resistant Na(+) currents. In whole-cell current-clamp recordings, the sustained excitability evoked by PAR(2) activation was blocked by the PKC inhibitor, calphostin, and the ERK(1/2) inhibitor PD98059. Studies of ERK(1/2) phosphorylation using confocal microscopy demonstrated that SLIGRL-NH(2) increased levels of immunoreactive pERK(1/2) in DRG neurons, particularly in proximity to the plasma membrane. Thus, activation of PAR(2) receptors on colonic nociceptive neurons causes sustained hyperexcitability that is related, at least in part, to suppression of delayed rectifier I(K) currents. Both PKC and ERK(1/2) mediate the PAR(2)-induced hyperexcitability. These studies describe a novel mechanism of sensitization of colonic nociceptive neurons that may be implicated in conditions of visceral hyperalgesia such as irritable bowel syndrome.

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A method of automatically identifying and tracking polar-cap plasma patches, utilising data inversion and feature-tracking methods, is presented. A well-established and widely used 4-D ionospheric imaging algorithm, the Multi-Instrument Data Assimilation System (MIDAS), inverts slant total electron content (TEC) data from ground-based Global Navigation Satellite System (GNSS) receivers to produce images of the free electron distribution in the polar-cap ionosphere. These are integrated to form vertical TEC maps. A flexible feature-tracking algorithm, TRACK, previously used extensively in meteorological storm-tracking studies is used to identify and track maxima in the resulting 2-D data fields. Various criteria are used to discriminate between genuine patches and "false-positive" maxima such as the continuously moving day-side maximum, which results from the Earth's rotation rather than plasma motion. Results for a 12-month period at solar minimum, when extensive validation data are available, are presented. The method identifies 71 separate structures consistent with patch motion during this time. The limitations of solar minimum and the consequent small number of patches make climatological inferences difficult, but the feasibility of the method for patches larger than approximately 500 km in scale is demonstrated and a larger study incorporating other parts of the solar cycle is warranted. Possible further optimisation of discrimination criteria, particularly regarding the definition of a patch in terms of its plasma concentration enhancement over the surrounding background, may improve results.

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Resistant starch (RS) has been shown to beneficially affect insulin sensitivity in healthy individuals and those with metabolic syndrome, but its effects on human type 2 diabetes (T2DM) are unknown. This study aimed to determine the effects of increased RS consumption on insulin sensitivity and glucose control and changes in postprandial metabolites and body fat in T2DM. Seventeen individuals with well-controlled T2DM (HbA1c 46.6±2 mmol/mol) consumed, in a random order, either 40 g of type 2 RS (HAM-RS2) or a placebo, daily for 12 weeks with a 12-week washout period in between. At the end of each intervention period, participants attended for three metabolic investigations: a two-step euglycemic–hyperinsulinemic clamp combined with an infusion of [6,6-2H2] glucose, a meal tolerance test (MTT) with arterio-venous sampling across the forearm, and whole-body imaging. HAM-RS2 resulted in significantly lower postprandial glucose concentrations (P=0.045) and a trend for greater glucose uptake across the forearm muscle (P=0.077); however, there was no effect of HAM-RS2 on hepatic or peripheral insulin sensitivity, or on HbA1c. Fasting non-esterified fatty acid (NEFA) concentrations were significantly lower (P=0.004) and NEFA suppression was greater during the clamp with HAM-RS2 (P=0.001). Fasting triglyceride (TG) concentrations and soleus intramuscular TG concentrations were significantly higher following the consumption of HAM-RS2 (P=0.039 and P=0.027 respectively). Although fasting GLP1 concentrations were significantly lower following HAM-RS2 consumption (P=0.049), postprandial GLP1 excursions during the MTT were significantly greater (P=0.009). HAM-RS2 did not improve tissue insulin sensitivity in well-controlled T2DM, but demonstrated beneficial effects on meal handling, possibly due to higher postprandial GLP1.