Mol Pain
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We recently used Nav1.8-ChR2 mice in which Nav1.8-expressing afferents were optogenetically tagged to classify mechanosensitive afferents into Nav1.8-ChR2-positive and Nav1.8-ChR2-negative mechanoreceptors. We found that the former were mainly high threshold mechanoreceptors (HTMRs), while the latter were low threshold mechanoreceptors (LTMRs). In the present study, we further investigated whether the properties of these mechanoreceptors were altered following tissue inflammation. ⋯ Spontaneous action potential impulses were not observed in Nav1.8-ChR2-positive Aβ-fiber mechanoreceptors but occurred in Nav1.8-ChR2-negative Aβ-fiber mechanoreceptors with a lower mechanical threshold in the saline goup, and a higher mechanical threshold in the CFA group. No significant change was observed in the mechanical sensitivity of Nav1.8-ChR2-positive and Nav1.8-ChR2-negative Aδ-fiber mechanoreceptors and Nav1.8-ChR2-positive C-fiber mechanoreceptors following hind paw inflammation. Collectively, inflammation significantly altered the functional properties of both Nav1.8-ChR2-positive and Nav1.8-ChR2-negative Aβ-fiber mechanoreceptors, which may contribute to mechanical allodynia during inflammation.
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Chondromalacia, characterized by the softening of cartilage, is a prevalent condition affecting joint health with complex etiology. The immune system's role in its pathogenesis has been implicated but remains to be fully elucidated. To address a critical knowledge gap, we conducted a two-sample Mendelian randomization analysis of 731 immune cell phenotypes, assessing parameters like fluorescence, cell count, and morphology. ⋯ This breakthrough sheds light on the pathophysiological mechanisms of the condition. The identification of protective and risk-associated immune cell phenotypes provides a foundation for further exploration of immunological mechanisms in chondromalacia and may pave the way for targeted interventions. Future research is warranted to validate these findings and explore their clinical implications.
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Cancer-induced bone pain (CIBP) is one of the most common and feared symptoms in patients with advanced tumors. The X-C motif chemokine ligand 12 (CXCL12) and the CXCR4 receptor have been associated with glial cell activation in bone cancer pain. Moreover, mitogen-activated protein kinases (MAPKs), as downstream CXCL12/CXCR4 signals, and c-Jun, as activator protein AP-1 components, contribute to the development of various types of pain. ⋯ Immunofluorescence images showed activated microglia in the spinal cord on day 14 after TCI and co-expression of CXCL12/CXCR4, p-MAPKs (p-JNK, p-ERK, p-p38 MAPK), and p-c-Jun in microglia. Intrathecal injection of the CXCR4 inhibitor AMD3100 reduced JNK and c-Jun phosphorylations, and intrathecal injection of the JNK inhibitor SP600125 and esketamine also alleviated TCI-induced pain and reduced the expression of p-JNK and p-c-Jun in microglia. Overall, our data suggest that the CXCL12/CXCR4-JNK-c-Jun signaling pathway of microglia in the spinal cord mediates neuronal sensitization and pain hypersensitivity in cancer-induced bone pain and that esketamine exerts its analgesic effect by inhibiting the JNK-c-Jun pathway.
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In vivo analysis of protein function in nociceptor subpopulations using antisense oligonucleotides and short interfering RNAs is limited by their non-selective cellular uptake. To address the need for selective transfection methods, we covalently linked isolectin B4 (IB4) to streptavidin and analyzed whether it could be used to study protein function in IB4(+)-nociceptors. ⋯ This knockdown in PKCε expression in IB4(+) DRG neurons is sufficient to reverse hyperalgesic priming, a rodent model of chronic pain that is dependent on PKCε in IB4(+)-nociceptors. These results establish that IB4-streptavidin can be used to study protein function in a defined subpopulation of nociceptive C-fiber afferents.
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Long-term pain is a common health problem that results in disability for patients of all ages, leading to an enormous economic burden. Over 20% of the population suffer from long-term pain. Unfortunately, there are no clinical tests that predicts who will develop long-term pain. The overall aim is to predict future pain incidence based on brain function, pain behavior, health status, and genetic variability. ⋯ Results indicate that a superstruct design is feasible for collecting a large number of high-quality data. The incidence of long-term pain indicates that a sufficient number of participants have been recruited to complete the prediction analyses. PrePain is a unique prospective pain database with a fair prognosis to determine risk factors of long-term pain.