Pain
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Paradoxical associations have been observed for leisure-time physical activity (LTPA) and occupational physical activity (OPA) and several health-related outcomes. Typically, higher LTPA is associated with health benefits and high OPA with health hazards. Using data from the Tromsø Study (2015-2016), we assessed how questionnaire-based LTPA and OPA (n = 21,083) and accelerometer-measured physical activity (PA) (n = 6778) relate to pain outcomes. ⋯ Higher levels of accelerometer-measured PA were associated with less pain. To summarize, we found inverse associations for LTPA and OPA. Benefits from LTPA seem to depend on low levels of OPA.
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This study set out to investigate in a population-based longitudinal cohort, whether chronification of back pain (BP) is related to structural gray matter changes in corticolimbic brain structures. Gray matter volume (GMV) was measured in participants with chronic BP (CBP, n = 168) and controls without chronic pain (n = 323) at 2 time points with an interval of 7 years (baseline t1, follow-up t2). Over this time period, participants with CBP showed an increase of GMV in the left ventral striatum, whereas controls showed a decrease. ⋯ Those with emerging CBP had less GMV in the right entorhinal area, right amygdala, and left medial frontal cortex. Additional variables differing between those who had BP at t1 and later developed CBP or not were pain intensity, body mass index, and depression score. In sum, these findings are in accordance with the notion that limbic brain properties are both predisposing risk factors and drivers of brain reorganization during the development of CBP.
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Over the past 2 decades, the microbiome has received increasing attention for the role that it plays in health and disease. Historically, the gut microbiome was of particular interest to pain scientists studying nociplastic visceral pain conditions given the anatomical juxtaposition of these microorganisms and the neuroimmune networks that drive pain in such diseases. More recently, microbiomes both inside and across the surface of the body have been recognized for driving sensory symptoms in a broader set of diseases. ⋯ This review specifically details the animal species, injury models, behavior measures, and microbiome manipulations used in preclinical pain research. From this analysis, we were also able to conclude how manipulations of the microbiome alter pain thresholds in naïve animals and persistent pain intensity and duration in cutaneous and visceral pain models. This review summarizes by identifying existing gaps in the literature and providing recommendations for how to best plan, implement, and interpret data collected in preclinical microbiome pain experiments.
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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.