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Pain experience can change the central processing of nociceptive inputs, resulting in persistent allodynia and hyperalgesia. However, the underlying circuit mechanisms remain underexplored. Here, we focus on pain-induced remodeling of the projection from the mediodorsal thalamus (MD) to anterior cingulate cortex (ACC), a projection that relays spinal nociceptive input for central processing. Using optogenetics combined with slice electrophysiology, we detected in male mice that 7 days of chronic constriction injury (CCI; achieved by loose ligation of the sciatic nerve) generated AMPA receptor (AMPAR)-silent glutamatergic synapses within the contralateral MD-to-ACC projection. AMPAR-silent synapses are typically GluN2B-enriched nascent glutamatergic synapses that mediate the initial formation of neural circuits during early development. During development, some silent synapses mature and become 'unsilenced' by recruiting and stabilizing AMPARs, consolidating and strengthening the newly formed circuits. Consistent with these synaptogenic features, pain-induced generation of silent synapses was accompanied by increased densities of immature dendritic spines in ACC neurons and increased synaptic weight of GluN2B-containing NMDA receptors (NMDARs) in the MD-to-ACC projection. After prolonged (∼30 days) CCI, injury-generated silent synapses declined to low levels, which likely resulted from a synaptic maturation process that strengthens AMPAR-mediated MD-to-ACC transmission. Consistent with this hypothesis, viral-mediated knockdown of GluN2B in ACC neurons, which prevented pain-induced generation of silent synapses and silent synapse-mediated strengthening of MD-to-ACC projection after prolonged CCI, prevented the development of allodynia. Taken together, our results depict a silent synapse-mediated mechanism through which key supraspinal neural circuits that regulate pain sensitivity are remodeled to induce allodynia and hyperalgesia.
Learn More >A small number of studies have supported the efficacy of open-label placebos (OLPs) in reducing pain. However, research comparing the effectiveness of OLPs with deceptive placebos (DPs) is limited, and the relative impact on pain tolerance versus intensity are not yet understood. This study therefore, examined the effectiveness of a nasal placebo administered openly and deceptively on pain intensity and tolerance during a cold pressor test (CPT).
Learn More >Examine factors associated with post-procedure opioid receipt and persistent opioid use among opioid-naïve patients in a nationally representative sample SUMMARY BACKGROUND DATA:: We used panels 18-20 in the Medical Expenditures Panel Survey (MEPS) between the years 2013 to 2015. Respondents ages 18 and over with any self-reported procedure in the previous year with complete data on the outcome variables for the remainder of the two-year study period.
Learn More >In the last decade, machine learning has been widely used in different fields, especially because of its capacity to work with complex data. With the support of machine learning techniques, different studies have been using data-driven approaches to better understand some syndromes like mild cognitive impairment, Alzheimer's disease, schizophrenia, and chronic pain. Chronic pain is a complex disease that can recurrently be misdiagnosed due to its comorbidities with other syndromes with which it shares symptoms. Within that context, several studies have been suggesting different machine learning algorithms to classify or predict chronic pain conditions. Those algorithms were fed with a diversity of data types, from self-report data based on questionnaires to the most advanced brain imaging techniques. In this study, we assessed the sensitivity of different algorithms and datasets classifying chronic pain syndromes. Together with this assessment, we highlighted important methodological steps that should be taken into account when an experiment using machine learning is conducted. The best results were obtained by ensemble-based algorithms and the dataset containing the greatest diversity of information, resulting in area under the receiver operating curve (AUC) values of around 0.85. In addition, the performance of the algorithms is strongly related to the hyper-parameters. Thus, a good strategy for hyper-parameter optimization should be used to extract the most from the algorithm. These findings support the notion that machine learning can be a powerful tool to better understand chronic pain conditions.
Learn More >The pathophysiology of headaches associated with rhinosinusitis is poorly known. Since the generation of headaches is thought to be linked to the activation of intracranial afferents, we used an animal model to characterise spinal trigeminal neurons with nociceptive input from the dura mater and paranasal sinuses.
Learn More >To examine the effect of sex on migraine trigger factors.
Learn More >Pharmacological treatment of cluster headache constitutes the core of clinical management, but evidence is sparse. We aimed to generate insight in the existing treatment and identify associations between clinical features and treatment response.
Learn More >Migraine is associated with an increased risk of ischemic stroke. The associations are stronger in migraine with aura than in migraine without aura, in women than in men, and in younger subjects. However, the mechanisms by which migraine might increase the risk of ischemic stroke are debated.
Learn More >Most migraine patients report neck pain as part of their migraine symptomatology, but it is unknown whether triggering neck pain would induce migraine attacks. Our aim was to assess the occurrence of headache and/or neck pain after an endurance test of the neck muscles among migraineurs and controls.
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