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Peripheral nerve injuries affect millions of people per year and cause loss of sensation and muscle control alongside chronic pain. The most severe injuries are treated through a nerve autograft; however, donor site morbidity and poor outcomes mean alternatives are required. One option is to engineer nerve replacement tissues to provide a supportive microenvironment to encourage nerve regeneration as an alternative to nerve grafts. Currently, progress is hampered due to a lack of consensus on how to arrange materials and cells in space to maximize rate of regeneration. This is compounded by a reliance on experimental testing, which precludes extensive investigations of multiple parameters due to time and cost limitations. Here, a computational framework is proposed to simulate the growth of repairing neurites, captured using a random walk approach and parameterized against literature data. The framework is applied to a specific scenario where the engineered tissue comprises a collagen hydrogel with embedded biomaterial fibres. The size and number of fibres are optimized to maximize neurite regrowth, and the robustness of model predictions is tested through sensitivity analyses. The approach provides an tool to inform the design of engineered replacement tissues, with the opportunity for further development to multi-cue environments.
Learn More >Pain-related sensory input is processed in the spinal dorsal horn (SDH) before being relayed to the brain. That processing profoundly influences whether stimuli are correctly or incorrectly perceived as painful. Significant advances have been made in identifying the types of excitatory and inhibitory neurons that comprise the SDH, and there is some information about how neuron types are connected, but it remains unclear how the overall circuit processes sensory input or how that processing is disrupted under chronic pain conditions. To explore SDH function, we developed a computational model of the circuit that is tightly constrained by experimental data. Our model comprises conductance-based neuron models that reproduce the characteristic firing patterns of spinal neurons. Excitatory and inhibitory neuron populations, defined by their expression of genetic markers, spiking pattern, or morphology, were synaptically connected according to available qualitative data. Using a genetic algorithm, synaptic weights were tuned to reproduce projection neuron firing rates (model output) based on primary afferent firing rates (model input) across a range of mechanical stimulus intensities. Disparate synaptic weight combinations could produce equivalent circuit function, revealing degeneracy that may underlie heterogeneous responses of different circuits to perturbations or pathological insults. To validate our model, we verified that it responded to reduction of inhibition (i.e. disinhibition) and ablation of specific neuron types in a manner consistent with experiments. Thus validated, our model offers a valuable resource for interpreting experimental results and testing hypotheses to plan experiments for examining normal and pathological SDH circuit function.We developed a multiscale computer model of the posterior part of spinal cord gray matter (spinal dorsal horn), involved in perception of touch and pain. The model reproduces several experimental observations and makes predictions about how specific types of spinal neurons and synapses influence projection neurons that send information to the brain. Misfiring of these projection neurons can produce anomalous sensations associated with chronic pain. Our computer model will not only assist in planning future experiments, but will also be useful for developing new pharmacotherapy for chronic pain disorders, connecting the effect of drugs acting at the molecular scale with emergent properties of neurons and circuits that shape the pain experience.
Learn More >The switching variability caused by intrinsic stochasticity of the ionic/atomic motions during the conductive filaments (CFs) formation process largely limits the applications of diffusive memristors (DMs), including artificial neurons, neuromorphic computing and artificial sensory systems. In this study, a DM device with improved device uniformity based on well-crystallized two-dimensional (2D) h-BN, which can restrict the CFs formation from three to two dimensions due to the high migration barrier of Ag between h-BN interlayer, is developed. The BN-DM has potential arrayable feature with high device yield of 88%, which can be applied for building a reservoir computing system for digital pattern recognition with high accuracy rate of 96%, and used as an artificial nociceptor to sense the external noxious stimuli and mimic the important biological nociceptor properties. By connecting the BN-DM to a self-made triboelectric nanogenerator (TENG), a self-power mechano-nociceptor system, which can successfully mimic the important nociceptor features of "threshold", "relaxation" and "allodynia" is designed.
Learn More >The roles and connectivity of specific types of neurons within the spinal cord dorsal horn (DH) are being delineated at a rapid rate to provide an increasingly detailed view of the circuits underpinning spinal pain processing. However, the effects of these connections for broader network activity in the DH remain less well understood because most studies focus on the activity of single neurons and small microcircuits. Alternatively, the use of microelectrode arrays (MEAs), which can monitor electrical activity across many cells, provides high spatial and temporal resolution of neural activity. Here, the use of MEAs with mouse spinal cord slices to study DH activity induced by chemically stimulating DH circuits with 4-aminopyridine (4-AP) is described. The resulting rhythmic activity is restricted to the superficial DH, stable over time, blocked by tetrodotoxin, and can be investigated in different slice orientations. Together, this preparation provides a platform to investigate DH circuit activity in tissue from naïve animals, animal models of chronic pain, and mice with genetically altered nociceptive function. Furthermore, MEA recordings in 4-AP-stimulated spinal cord slices can be used as a rapid screening tool to assess the capacity of novel antinociceptive compounds to disrupt activity in the spinal cord DH.
Learn More >Bleeding is a potential complication after neuraxial and peripheral nerve blocks. The risk is increased in patients on antiplatelet and anticoagulant drugs. This joint guideline from the European Society of Anaesthesiology and Intensive Care and the European Society of Regional Anaesthesia aims to provide an evidence-based set of recommendations and suggestions on how to reduce the risk of antithrombotic drug-induced haematoma formation related to the practice of regional anaesthesia and analgesia.
Learn More >Urothelial cells of the urinary bladder play a critical role in the development and progression of interstitial cystitis/bladder pain syndrome (IC/BPS), a chronic and debilitating inflammatory disease. Given the lack of data on the exact phenotype and function of urothelial cells in an inflammatory setting (as in IC/BPS), we performed the first in-depth characterization of these cells using RNA sequencing, qPCR, ELISA, Western blot, and immunofluorescence. After TNFα stimulation, urothelial cells in the model of IC/BPS showed marked upregulation of several proinflammatory mediators, such as SAA, C3, IFNGR1, IL1α, IL1β, IL8, IL23A, IL32, CXCL1, CXCL5, CXCL10, CXCL11, TNFAIPR, TNFRSF1B, and BIRC3, involved in processes and pathways of innate immunity, including granulocyte migration and chemotaxis, inflammatory response, and complement activation, as well as TLR-, NOD-like receptor- and NFkB-signaling pathways, suggesting their active role in shaping the local immune response of the bladder. Our study demonstrates that the TNFα-stimulated urothelial cells recapitulate key observations found in the bladders of patients with IC/BPS, underpinning their utility as a suitable model for understanding IC/BPS mechanisms and confirming the role of TNFα signaling as an important component of the associated pathology. The present study also identifies novel upregulated gene targets of TNFα in urothelial cells, including genes encoding the acute phase protein SAA, complement component C3, and the cytokine receptor IFNGR1, which could be exploited as therapeutic targets of IC/BPS. Altogether, our study provides a reference database of the phenotype of urothelial cells in an inflammatory environment that will not only increase our knowledge of their role in IC/BPS, but also advance our understanding of how urothelial cells shape tissue immunity in the bladder.
Learn More >Responsive to treatment individually, chronic migraine remains strikingly resistant collectively, incurring the second-highest population burden of disability worldwide. A heterogeneity of responsiveness, requiring prolonged-currently heuristic-individual evaluation of available treatments, may reflect a diversity of causal mechanisms, or the failure to identify the most important, single causal factor. Distinguishing between these possibilities, now possible through the application of complex modelling to large-scale data, is critical to determine the optimal approach to identify new interventions in migraine and making the best use of existing ones. Examining a richly phenotyped cohort of 1446 consecutive unselected patients with chronic migraine, here we use causal multitask Gaussian process models to estimate individual treatment effects across 10 classes of preventatives. Such modelling enables us to quantify the accessibility of heterogeneous responsiveness to high-dimensional modelling, to infer the likely scale of the underlying causal diversity. We calculate the treatment effects in the overall population, and the conditional treatment effects among those modelled to respond and compare the true response rates between these two groups. Identifying a difference in response rates between the groups supports a diversity of causal mechanisms. Moreover, we propose a data-driven machine prescription policy, estimating the time-to-response when sequentially trialling preventatives by individualized treatment effects and comparing it to expert guideline sequences. All model performances are quantified out-of-sample. We identify significantly higher true response rates among individuals modelled to respond, compared with the overall population (mean difference of 0.034; 95% confidence interval 0.003-0.065; = 0.033), supporting significant heterogeneity of responsiveness and diverse causal mechanisms. The machine prescription policy yields an estimated 35% reduction in time-to-response (3.750 months; 95% confidence interval 3.507-3.993; < 0.0001) compared with expert guidelines, with no substantive increase in expense per patient. We conclude that the highly distributed mode of causation in chronic migraine necessitates high-dimensional modelling for optimal management. Machine prescription should be considered an essential clinical decision-support tool in the future management of chronic migraine.
Learn More >The perceiving mind constructs our coherent and embodied experience of the world from noisy, ambiguous and multi-modal sensory information. In this paper, we adopt the perspective that the experience of pain may similarly be the result of a probabilistic, inferential process. Prior beliefs about pain, learned from past experiences, are combined with incoming sensory information in a Bayesian manner to give rise to pain perception. Chronic pain emerges when prior beliefs and likelihoods are biased towards inferring pain from a wide range of sensory data that would otherwise be perceived as harmless. We present a computational model of interoceptive inference and pain experience. It is based on a Bayesian graphical network which comprises a hidden layer, representing the inferred pain state; and an observable layer, representing current sensory information. Within the hidden layer, pain states are inferred from a combination of priors , transition probabilities between hidden states and likelihoods of certain observations . Using variational inference and free-energy minimization, the model is able to learn from observations over time. By systematically manipulating parameter settings, we demonstrate that the model is capable of reproducing key features of both healthy- and chronic pain experience. Drawing on mathematical concepts, we finally simulate treatment resistant chronic pain and discuss mathematically informed treatment options.
Learn More >As a promising neuromodulation technique, vagus nerve stimulation (VNS) has been utilized to treat diverse diseases and the number of VNS studies has grown prosperously. Nonetheless, publication trends and research hotspots in this field remain unknown. This study aimed to perform a bibliometric analysis to systematically identify publication trends and research hotspots in VNS research within a 20-year panorama.
Learn More >Transcranial magnetic stimulation, as a relatively new type of treatment, is a safe and non-invasive method for pain therapy. Here, we used CiteSpace software to visually analyze 440 studies concerning transcranial magnetic stimulation in pain research from 2010 to 2021, indexed by Web of Science, to clarify the research hotspots in different periods and characterize the process of discovery in this field. The United States ranked first in this field. Lefaucheur JP, Fregni F, and Andrade ACD made great contributions to this field of study. The most prolific institution was University of São Paulo. The four main hot keywords were neuropathic pain, motor cortex, connectivity, and non-invasive brain stimulation. There were three main points that were generally accepted: (1) definite analgesic effect of high-frequency rTMS of M1 contralateral to pain side in neuropathic pain; (2) there are inconclusive recommendations regarding rTMS of the dorsolateral prefrontal cortex (DLPFC) in fibromyalgia and neuropathic pain; (3) there is low-quality evidence that single doses of high-frequency rTMS of the motor cortex may have short-term effects on chronic pain. This bibliometric analysis indicated that prospective, multi-center, large-sample, randomized controlled trials are still needed to further verify the effectiveness of various transcranial magnetic stimulation parameters in pain research.
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