Accepted

Fibromyalgia (FM) is a disease characterized by chronic widespread pain, fatigue, aches, joint stiffness, depression, cognitive dysfunction and non-restorative sleep. In FM, neurotransmission and glial activation can occur with an increase in inflammatory cytokines and involvement of mast cells (MCs) in the skin. FM skin biopsies show an increased number of MCs, as well as the production of corticotropin releasing hormone (CRH) and substance P (SP) by the neurons, which in turn activate MCs to release neurosensitizing pro-inflammatory substances, such as cytokines, secreted preformed mediators and lipids, which can exacerbate low-grade inflammation. In fact, certain pro-inflammatory cytokines are higher in FM and mediate muscle pain, the mechanism of which is not yet clear. MC-derived tumor necrosis factor (TNF) induces nerve growth factor (NGF) and participates in nerve fiber elongation in skin hypersensitivity. IL-37 is an inhibitor of pro-inflammatory IL-1 family members which are generated and released by MCs. The goal of this article is to demonstrate that inflammatory cytokines and MC products play a role in fibromyalgia and that inflammation may be inhibited by IL-37. Here, we propose IL-37 as a cytokine that contributes to improve the pathogenesis of FM by blocking IL-1 family members. This article is protected by copyright. All rights reserved.

This review summarizes major findings and recent advances in magnetic resonance spectroscopy (MRS) of migraine. A multi database search of PubMed, EMBASE, and Web of Science was performed with variations of magnetic resonance spectroscopy and headache until 20th September 2021. The search generated 2897 studies, 676 which were duplicates and 1836 were not related to headache. Of the remaining 385 studies examined, further exclusions for not migraine (n = 114), and not MRS of human brain (n = 128), and non-original contributions (n = 51) or conferences (n = 24) or case studies (n = 11) or non-English (n = 3), were applied. The manuscripts of all resulting reports were reviewed for their possible inclusion in this manuscript (n = 54). The reference lists of all included reports were carefully reviewed and articles relevant to this review were added (n = 2).Included are 56 studies of migraine with and without aura that involve magnetic resonance spectroscopy of the human brain. The topics are presented in the form of a narrative review. This review aims to provide a summary of the metabolic changes measured by MRS in patients with migraine. Despite the variability reported between studies, common findings focused on regions functionally relevant to migraine such as occipital cortices, thalamic nuclei, cerebellum and cingulate. The most reproducible results were decreased -acetyl-aspartate (NAA) in cerebellum in patients with hemiplegic migraine and in the thalamus of chronic migraine patients. Increased lactate (Lac) in the occipital cortex was found for migraine with aura but not in subjects without aura. MRS studies support the hypothesis of impaired energetics and mitochondrial dysfunction in migraine. Although results regarding GABA and Glu were less consistent, studies suggest there might be an imbalance of these important inhibitory and excitatory neurotransmitters in the migraine brain. Multinuclear imaging studies in migraine with and without aura, predominantly investigating phosphorous, report alterations of PCr in occipital, parietal, and posterior brain regions. There have been too few studies to assess the diagnostic relevance of sodium imaging in migraine.

The collection of increasing amounts of data in health care has become relevant for pain therapy and research. This poses problems for analyses with classical approaches, which is why artificial intelligence (AI) and machine learning (ML) methods are being included into pain research. The current literature on AI and ML in the context of pain research was automatically searched and manually curated. Common machine learning methods and pain settings covered were evaluated. Further focus was on the origin of the publication and technical details, such as the included sample sizes of the studies analyzed with ML. Machine learning was identified in 475 publications from 18 countries, with 79% of the studies published since 2019. Most addressed pain conditions included low back pain, musculoskeletal disorders, osteoarthritis, neuropathic pain, and inflammatory pain. Most used ML algorithms included random forests and support vector machines; however, deep learning was used when medical images were involved in the diagnosis of painful conditions. Cohort sizes ranged from 11 to 2,164,872, with a mode at n = 100; however, deep learning required larger data sets often only available from medical images. Artificial intelligence and ML, in particular, are increasingly being applied to pain-related data. This report presents application examples and highlights advantages and limitations, such as the ability to process complex data, sometimes, but not always, at the cost of big data requirements or black-box decisions.

Medicinal cannabis is prescribed in Australia for patients with chronic refractory pain conditions. However, measures of safety and effectiveness of different cannabinoids are lacking. We designed an observational study to capture effectiveness, adverse events (AEs), and health-related quality of life (HRQoL) measures in patients prescribed an oral medicinal cannabis formulation at Cannabis Access Clinics through the Cannabis Access Clinics Observational study (CACOS).

The cholecystokinin receptor system, specifically cholecystokinin 2 receptor (CCK2R) is a historic target for pain management that has shown limited success. However, new approaches to target CCK2R have incited fresh enthusiasm for this target. In this mini-review, we discuss what is known about CCK2R in peripheral and central circuits under naïve physiological conditions and under conditions of chronic pain, the interactions of CCK2Rs with opioids and briefly, recent efforts to develop new treatments targeting CCK2R for chronic pain.