The chemerin receptor 23 agonist, chemerin, attenuates monosynaptic C-fibre input to lamina I neurokinin 1 receptor expressing rat spinal cord neurons in inflammatory pain

BACKGROUND: Recent evidence has shown that the chemerin receptor 23 (ChemR23) represents a novel inflammatory pain target, whereby the ChemR23 agonists, resolvin E1 and chemerin, can inhibit inflammatory pain hypersensitivity, by a mechanism that involves normalisation of potentiated spinal cord responses. This study has examined the ability of the ChemR23 agonist, chemerin, to modulate synaptic input to lamina I neurokinin 1 receptor expressing (NK1R+) dorsal horn neurons, which are known to be crucial for the manifestation of inflammatory pain. RESULTS: Whole-cell patch-clamp recordings from pre-identified lamina I NK1R+ neurons, in rat spinal cord slices, revealed that chemerin significantly attenuates capsaicin potentiation of miniature excitatory postsynaptic current (mEPSC) frequency, but is without effect in non-potentiated conditions. In tissue isolated from complete Freund’s adjuvant (CFA) treated rats, chemerin significantly reduced the peak amplitude of monosynaptic C-fibre evoked excitatory postsynaptic currents (eEPSCs) in a subset of lamina I NK1R+ neurons, termed chemerin responders. However, chemerin did not alter the peak amplitude of monosynaptic C-fibre eEPSCs in control tissue. Furthermore, paired-pulse recordings in CFA tissue demonstrated that chemerin significantly reduced paired-pulse depression in the subset of neurons classified as chemerin responders, but was without effect in non-responders, indicating that chemerin acts presynaptically to attenuate monosynaptic C-fibre input to a subset of lamina I NK1R+ neurons. CONCLUSIONS: These results suggest that the reported ability of ChemR23 agonists to attenuate inflammatory pain hypersensitivity may in part be due to a presynaptic inhibition of monosynaptic C-fibre input to lamina I NK1R+ neurons and provides further evidence that ChemR23 represents a promising inflammatory pain target

Visual parameter optimisation for biomedical image processing

Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches

RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses

The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium and providing VIS support to various observational, analytical, model-developmental, and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses

RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses

The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium and providing VIS support to various observational, analytical, model-developmental, and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses

A Rapamycin-Sensitive Signaling Pathway Is Essential for the Full Expression of Persistent Pain States

Translational control through the mammalian target of rapamycin (mTOR) is critical for synaptic plasticity, cell growth and axon guidance. Recently, it was also shown that mTOR signaling was essential for the maintenance of the sensitivity of subsets of adult sensory neurons. Here, we show that persistent pain states, but not acute pain behaviour, are substantially alleviated by centrally administered rapamycin, an inhibitor of the mTOR pathway. We demonstrate that rapamycin modulates nociception by acting on subsets of primary afferents and superficial dorsal horn neurons to reduce both primary afferent sensitivity and central plasticity. We found that the active form of mTOR is present in a subpopulation of myelinated dorsal root axons, but rarely in unmyelinated C- fibers, and heavily expressed in the dorsal horn by lamina I/III projection neurons that are known to mediate the induction and maintenance of pain states. Intrathecal injections of rapamycin inhibited the activation of downstream targets of mTOR in dorsal horn and dorsal roots and reduced the thermal sensitivity of A- fibers. Moreover, in vitro studies showed that rapamycin increased the electrical activation threshold of Aδ- fibers in dorsal roots. Taken together our results imply that central rapamycin reduces neuropathic pain by acting both on an mTOR positive subset of A- nociceptors and lamina I projection neurons and suggest a new pharmacological route for therapeutic intervention in persistent pain states

A putative relay circuit providing low-threshold mechanoreceptive input to lamina I projection neurons via vertical cells in lamina II of the rat dorsal horn

Background: Lamina I projection neurons respond to painful stimuli, and some are also activated by touch or hair movement. Neuropathic pain resulting from peripheral nerve damage is often associated with tactile allodynia (touch-evoked pain), and this may result from increased responsiveness of lamina I projection neurons to non-noxious mechanical stimuli. It is thought that polysynaptic pathways involving excitatory interneurons can transmit tactile inputs to lamina I projection neurons, but that these are normally suppressed by inhibitory interneurons. Vertical cells in lamina II provide a potential route through which tactile stimuli can activate lamina I projection neurons, since their dendrites extend into the region where tactile afferents terminate, while their axons can innervate the projection cells. The aim of this study was to determine whether vertical cell dendrites were contacted by the central terminals of low-threshold mechanoreceptive primary afferents. Results: We initially demonstrated contacts between dendritic spines of vertical cells that had been recorded in spinal cord slices and axonal boutons containing the vesicular glutamate transporter 1 (VGLUT1), which is expressed by myelinated low-threshold mechanoreceptive afferents. To confirm that the VGLUT1 boutons included primary afferents, we then examined vertical cells recorded in rats that had received injections of cholera toxin B subunit (CTb) into the sciatic nerve. We found that over half of the VGLUT1 boutons contacting the vertical cells were CTb-immunoreactive, indicating that they were of primary afferent origin. Conclusions: These results show that vertical cell dendritic spines are frequently contacted by the central terminals of myelinated low-threshold mechanoreceptive afferents. Since dendritic spines are associated with excitatory synapses, it is likely that most of these contacts were synaptic. Vertical cells in lamina II are therefore a potential route through which tactile afferents can activate lamina I projection neurons, and this pathway could play a role in tactile allodynia

Neuronal circuitry for pain processing in the dorsal horn

Neurons in the spinal dorsal horn process sensory information, which is then transmitted to several brain regions, including those responsible for pain perception. The dorsal horn provides numerous potential targets for the development of novel analgesics and is thought to undergo changes that contribute to the exaggerated pain felt after nerve injury and inflammation. Despite its obvious importance, we still know little about the neuronal circuits that process sensory information, mainly because of the heterogeneity of the various neuronal components that make up these circuits. Recent studies have begun to shed light on the neuronal organization and circuitry of this complex region

Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.

From Europe PMC via Jisc Publications RouterHistory: epub 2022-08-15, ppub 2022-10-01Publication status: PublishedFunder: UK Research and Innovation; Grant(s): ST/V006126/1, EP/V054236/1, EP/V033670/1We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs-a series of ideas, approaches and methods taken from existing visualization research and practice-deployed and developed to support modelling of the COVID-19 pandemic. Structured independent commentary on these efforts is synthesized through iterative reflection to develop: evidence of the effectiveness and value of visualization in this context; open problems upon which the research communities may focus; guidance for future activity of this type and recommendations to safeguard the achievements and promote, advance, secure and prepare for future collaborations of this kind. In describing and comparing a series of related projects that were undertaken in unprecedented conditions, our hope is that this unique report, and its rich interactive supplementary materials, will guide the scientific community in embracing visualization in its observation, analysis and modelling of data as well as in disseminating findings. Equally we hope to encourage the visualization community to engage with impactful science in addressing its emerging data challenges. If we are successful, this showcase of activity may stimulate mutually beneficial engagement between communities with complementary expertise to address problems of significance in epidemiology and beyond. See https://ramp-vis.github.io/RAMPVIS-PhilTransA-Supplement/. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'