Pain
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Parkinson disease (PD) affects up to 2% of the general population older than 65 years and is a major cause of functional loss. Chronic pain is a common nonmotor symptom that affects up to 80% of patients with (Pw) PD both in prodromal phases and during the subsequent stages of the disease, negatively affecting patient's quality of life and function. Pain in PwPD is rather heterogeneous and may occur because of different mechanisms. ⋯ This is also in line with the International Classification of Disease-11 , which acknowledges the possibility of chronic secondary musculoskeletal or nociceptive pain due to disease of the CNS. In this narrative review and opinion article, a group of basic and clinical scientists revise the mechanism of pain in PD and the challenges faced when classifying it as a stepping stone to discuss an integrative view of the current classification approaches and how clinical practice can be influenced by them. Knowledge gaps to be tackled by coming classification and therapeutic efforts are presented, as well as a potential framework to address them in a patient-oriented manner.
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Observing someone experience pain relief or exacerbation after an intervention may induce placebo hypoalgesia or nocebo hyperalgesia. Understanding the factors that contribute to these effects could help in the development of strategies for optimizing treatment of chronic pain conditions. We systematically reviewed and meta-analyzed the literature on placebo hypoalgesia and nocebo hyperalgesia induced by observational learning (OL). ⋯ Overall, the meta-analysis demonstrates that OL can shape placebo hypoalgesia and nocebo hyperalgesia. More research is needed to identify predictors of these effects and to study them in clinical populations. In the future, OL could be an important tool to help maximize placebo hypoalgesia in clinical settings.
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We investigated the efficacy of inhibiting persistent Na + currents (I NaP ) in acute rodent models of migraine with aura. Cortical spreading depression (SD) is a slow wave of neuronal and glial depolarization that underlies the migraine aura. Minimally invasive optogenetic SD (opto-SD) causes periorbital mechanical allodynia in mice, suggesting SD activates trigeminal nociceptors. ⋯ GS-458967 also diminished early and late phase formalin-induced paw-licking behavior with early phase paw licking responding to lower doses. GS-458967 up to 3 mg/kg had no impact on locomotor activity. These data provide evidence that I NaP inhibition can reduce opto-SD-induced trigeminal pain behavior and support I NaP inhibition as an antinociceptive strategy for both abortive and preventive treatment of migraine.
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Although founded on the basis of the study of pain, the International Association for the Study of Pain (IASP) has actively advocated for improving pain relief and access to pain management in a variety of ways. The Global Year was launched in 2004 and has continued with a different theme each year, and "Pain Awareness Month" is held every September. ⋯ The work of IASP on the 11th version of the International Classification of Disease has ensured that chronic pain is recognized as a disease in its own right, and the establishment of the Global Alliance of Partners for Pain Advocacy Task Force recognizes the importance of engaging people with lived experience of pain in accomplishing IASP's mission. The Working Group on Global Advocacy now spearheads IASP's global efforts in capacity building to ensure that pain advocacy activities will continue to grow.
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Multicenter Study
Brain morphology predicts individual sensitivity to pain: a multicenter machine learning approach.
Sensitivity to pain shows a remarkable interindividual variance that has been reported to both forecast and accompany various clinical pain conditions. Although pain thresholds have been reported to be associated to brain morphology, it is still unclear how well these findings replicate in independent data and whether they are powerful enough to provide reliable pain sensitivity predictions on the individual level. In this study, we constructed a predictive model of pain sensitivity (as measured with pain thresholds) using structural magnetic resonance imaging-based cortical thickness data from a multicentre data set (3 centres and 131 healthy participants). ⋯ Analysis of model coefficients suggests that the most robust cortical thickness predictors of pain sensitivity are the right rostral anterior cingulate gyrus, left parahippocampal gyrus, and left temporal pole. Cortical thickness in these regions was negatively correlated to pain sensitivity. Our results can be considered as a proof-of-concept for the capacity of brain morphology to predict pain sensitivity, paving the way towards future multimodal brain-based biomarkers of pain.