Articles: neuralgia.
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Voltage-gated sodium channel Nav1.7 has been validated as a perspective target for selective inhibitors with analgesic and anti-itch activity. The objective of this study was to discover new candidate compounds with Nav1.7 inhibitor properties. The authors hypothesized that their approach would yield at least one new compound that inhibits sodium currents in vitro and exerts analgesic and anti-itch effects in mice. ⋯ This study's computer-aided drug discovery approach yielded a new Nav1.7 inhibitor that shows analgesic and anti-pruritic activity in mouse models.
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Central post-stroke pain (CPSP) is chronic neuropathic pain due to a lesion or dysfunction of the central nervous system following cerebrovascular insult. This syndrome is characterized by chronic somatosensory abnormalities including spontaneous pain, hyperalgesia and allodynia, which localize to body areas corresponding to the injured brain region. However, despite its potential to impair activities of daily life and cause mood disorders after stroke, it is probably the least recognized complication of stroke. ⋯ Moreover, mounting evidence has revealed that EETs exert anti-inflammatory effects by inhibiting the expression of vascular adhesion molecules, activating NFκB, inflammatory cytokines secretion and COX-2 gene induction. The present review focuses on the extensive evidence supporting the potential of EETs to be a multi-functional therapeutic approach for CPSP. Additionally, the role of EETs in the crosstalk between anti-CPSP and the comorbid mood disorder is reviewed herein.
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Neuropathic pain (NP) remains a major debilitating condition affecting more than 26% of breast cancer survivors worldwide. NP is diagnosed using a validated 10-items Douleur Neuropathique - 4 screening questionnaire which is administered 3 months after surgery and requires patient-doctor interaction. To develop an effective prognosis model admissible soon after surgery, without the need for patient-doctor interaction, we sought to [1] identify specific pain characteristics that can help determine which patients may be susceptible to NP after BC surgery, and 2) assess the utility of machine learning models developed in objective [1] as a knowledge discovery tool for downstream analysis. ⋯ Modern machine learning models show improvements over traditional least square regression in predicting of DN4-interview score. Penalized regression methods and the Gradient boosting model out-perform other models. As a predictor discovery tool, machine learning algorithms identify relevant predictors for DN4-interview score that remain statistically significant indicators of neuropathic pain in the classification model. Anxiety, type of surgery and acute pain on movement remain the most useful predictors for neuropathic pain.