Pain
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Decoding pain: uncovering the factors that affect the performance of neuroimaging-based pain models.
Neuroimaging-based pain biomarkers, when combined with machine learning techniques, have demonstrated potential in decoding pain intensity and diagnosing clinical pain conditions. However, a systematic evaluation of how different modeling options affect model performance remains unexplored. This study presents the results from a comprehensive literature survey and benchmark analysis. ⋯ Specifically, incorporating more pain-related brain regions, increasing sample sizes, and averaging less data during training and more data during testing improved performance. These findings offer useful guidance for developing neuroimaging-based biomarkers, underscoring the importance of strategic selection of modeling approaches to build better-performing neuroimaging pain biomarkers. However, the generalizability of these findings to clinical pain requires further investigation.
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Menstrual pain is associated with deficits in central pain processing, yet neuroimaging studies to date have all been limited by focusing on group comparisons of adult women with vs without menstrual pain. This study aimed to investigate the role of the triple network model (TNM) of brain networks in adolescent girls with varied menstrual pain severity ratings. One hundred participants (ages 13-19 years) completed a 6-min resting state functional magnetic resonance imaging (fMRI) scan and rated menstrual pain severity, menstrual pain interference, and cumulative menstrual pain exposure. ⋯ In addition, menstrual pain interference was positively associated with connectivity within the left CEN, whereas connectivity both within the right CEN and between the right CEN and cortical areas outside the network (including the insula) were negatively associated with menstrual pain interference. Cumulative menstrual pain exposure shared a strong negative association with connectivity between the default mode network and other widespread regions associated with large-scale brain networks. These findings support a key role for the involvement of TNM brain networks in menstrual pain characteristics and suggest that alterations in pain processing exist in adolescents with varying levels of menstrual pain.
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As the incidence and survival rates of patients with cancer continues to grow, an increasing number of people are living with comorbidities, which often manifests as cancer-induced bone pain (CIBP). The majority of patients with CIBP report poor pain control from currently available analgesics. A conotoxin, Contulakin-G (CGX), has been demonstrated to be an antinociceptive agent in postsurgical and neuropathic pain states via a neurotensin receptor 2 (NTSR2)-mediated pathway. ⋯ Moreover, at antinociceptive doses, CGX had no impact on motor behavior in rodents with CIBP. Finally, RNAScope and immunoblotting analysis revealed expression of NTSR2 in both dorsal and ventral horns, while Cav2.3 was minimally expressed in the ventral horn, possibly explaining the sensory selectivity of CGX. Together, these findings support advancing CGX as a potential therapeutic for cancer pain.
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Spinal cord stimulation (SCS) is an effective modality for pain treatment, yet its underlying mechanisms remain elusive. Neurokinin 1 receptor-positive (NK1R + ) neurons in spinal lamina I play a pivotal role in pain transmission. To enhance our mechanistic understanding of SCS-induced analgesia, we investigated how different SCS paradigms modulate the activation of NK1R + neurons, by developing NK1R-Cre;GCaMP6s transgenic mice and using in vivo calcium imaging of superficial NK1R + neurons under anesthesia (1.5% isoflurane). ⋯ However, at low intensity (20% MoT), the 30-minute 900-Hz SCS only induced persistent neuronal inhibition in naïve mice, but not in SNI-t mice. In conclusion, both 10-minute high-intensity SCS and 30-minute SCS at moderate intensity inhibit the activation of superficial NK1R + neurons, potentially attenuating spinal nociceptive transmission. Furthermore, in vivo calcium imaging of NK1R + neurons provides a new approach for exploring the spinal neuronal mechanisms of pain inhibition by neuromodulation pain therapies.