Pain
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Understanding the development of chronic pain (CP) is challenging due to its multifactorial etiology. Child maltreatment (CM), encompassing various types of neglect and abuse affecting more than one-third of the population, is a critical aspect of early-life adversity with long-lasting impacts. It is increasingly recognized for its role in altering biopsychosocial processes, potentially increasing vulnerability to CP. ⋯ Importantly, biopsychosocial factors are found to explain over 60% of the association between CM and CP, with psychological factors playing a key role. This study not only characterizes the relationship between CM and CP but also underscores the influence of psychosocial elements in this dynamic interplay. These findings offer important insights into the long-term impacts of CM and provide a foundation for developing targeted therapeutic and preventive strategies for CP.
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Understanding the mechanisms that underpin the transition from acute to chronic pain is critical for the development of more effective and targeted treatments. There is growing interest in the contribution of glial cells to this process, with cross-sectional preclinical studies demonstrating specific changes in these cell types capturing targeted timepoints from the acute phase and the chronic phase. In vivo longitudinal assessment of the development and evolution of these changes in experimental animals and humans has presented a significant challenge. ⋯ These advances now permit tracking of glial changes over time and provide the ability to relate these changes to pain-relevant symptomology, comorbid psychiatric conditions, and treatment outcomes at both a group and an individual level. In this article, we summarize evidence for gliosis in the transition from acute to chronic pain and provide an overview of the specific radiotracers available to measure this process, highlighting their potential, particularly when combined with ex vivo / in vitro techniques, to understand the pathophysiology of chronic neuropathic pain. These complementary investigations can be used to bridge the existing gap in the field concerning the contribution of gliosis to neuropathic pain and identify potential targets for interventions.
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Nociplastic pain, characterized by abnormal pain processing without an identifiable organic cause, affects a significant portion of the global population. Unfortunately, current pharmacological treatments for this condition often prove ineffective, prompting the need to explore new potential targets for inducing analgesic effects in patients with nociplastic pain. In this context, toll-like receptors (TLRs), known for their role in the immune response to infections, represent promising opportunities for pharmacological intervention because they play a relevant role in both the development and maintenance of pain. ⋯ In addition, we explore the association between nociplastic pain and psychiatric comorbidities, proposing that modulating TLRs can potentially alleviate both pain syndromes and related psychiatric disorders. Finally, we discuss the potential sex differences in TLR signaling, considering the higher prevalence of nociplastic pain among women. Altogether, this review aims to shed light on nociplastic pain, its underlying mechanisms, and its intriguing relationship with TLR signaling pathways, ultimately framing the potential therapeutic role of TLRs in addressing this challenging condition.
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The variability in pain drawing styles and analysis methods has raised concerns about the reliability of pain drawings as a screening tool for nonpain symptoms. In this study, a data-driven approach to pain drawing analysis has been used to enhance the reliability. The aim was to identify distinct clusters of pain patterns by using latent class analysis (LCA) on 46 predefined anatomical areas of a freehand digital pain drawing. ⋯ Statistically significant differences were found between these clusters in every self-reported health domain. Similarly, for both LBP and MBPNP, pain drawings involving more extensive pain areas were associated with higher activity limitation, more intense pain, and more psychological distress. This study presents a versatile data-driven approach for analyzing pain drawings to assist in managing spinal pain.