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Enregistrement W4409826441 · doi:10.3389/fphar.2025.1605670

Editorial: Interplay between chronic pain and affective-cognitive alterations: shared neural mechanisms, circuits, and treatment

2025· editorial· en· W4409826441 sur OpenAlexaff
Luca Posa, Danilo De Gregorio, Serena Boccella, Kelly Smart

Notice bibliographique

RevueFrontiers in Pharmacology · 2025
Typeeditorial
Langueen
DomaineNeuroscience
ThématiquePain Management and Placebo Effect
Établissements canadiensCentre for Addiction and Mental Health
Organismes subventionnairesnon disponible
Mots-clésNeuroscienceChronic painBiological neural networkCognitionMedicinePsychologyCognitive psychology

Résumé

récupéré en direct d'OpenAlex

increased astrocyte activation at the chronic (4 weeks post-SNL) but not acute (1 week post-SNL) phase. Inhibiting astrocytes with fluorocitric acid (FCA) enhanced neuronal excitability by altering hyperpolarization-activated current without affecting synaptic transmission at the parabrachial nucleus-CeLC synapse. Behavioral tests showed that FCA influenced mechanical withdrawal thresholds and evoked vocalizations but did not alter facial grimacing or anxiety-like behaviors.These findings indicate astrocytes in the CeA may have protective functions in chronic neuropathic pain.Youqing Cai et al. explored the dorsal medial prefrontal cortex (dmPFC) to basolateral amygdala (BLA) pathway's role in emotional regulation. Optogenetic activation of this circuit in normal rats induced anxiety-and depression-like behaviors, while inhibition reduced anxiety and promoted reward-seeking behaviors. Their findings indicate the dmPFC-BLA circuit plays a critical role in mood regulation, with implications for pain-related emotional dysregulation.Several key brain areas and neurotransmitters mediate emotional and cognitive aspects of pain.Flores-Garcia et al. reviewed the ventral tegmental area (VTA) as a hub integrating pain and emotional processing. Mounting evidence suggests that the dopaminergic system within the VTA plays a pivotal role in chronic pain's affective components. The review emphasizes the importance of animal models incorporating both pain and mood disorder features to develop effective treatments. A review by Lançon and Seguela examined the anterior cingulate cortex (ACC) in topdown modulation of pain perception, focusing on monoaminergic pathways-dopamine (DA), norepinephrine (NE), and serotonin (5-HT). Chronic pain disrupts these neuromodulators, contributing to hyperexcitability and cognitive impairments. Understanding how these alterations affect pain perception could pave the way for novel, non-opioid-based therapies.Marino et al. used a machine learning (ML) approach to analyze central μ-opioid (μOR) and dopamine D2/D3 (DOR) receptor profiles in chronic migraine, a debilitating neurovascular pain disorder with a significant impact on cognitive and emotional functions. Using Compressive Big Data Analytics on data from positron emission tomography scans, they distinguished migraine patients from healthy controls with over 90% accuracy by identifying key predictive regions from each receptor system. For μOR, these regions included the anterior insula, thalamic nuclei, and putamen, while DOR dysfunction was primarily identified in the putamen. These findings offer insights into the neurochemical disruptions underlying migraine-related pain and cognitive impairments in humans.Corasaniti et al. assessed the efficacy of monoclonal antibodies (mAbs) targeting the calcitonin gene-related peptide (CGRP) or its receptor (CGRP-R) in treatment-resistant chronic migraine.Their real-world data suggest that combining anti-CGRP therapy with onabotulinumtoxin A reduces monthly headache days by ≥50% in 58.8% of patients. Erenumab, when combined with onabotulinumtoxin A, improved symptoms in 65% of cases, while eptinezumab was notable for its rapid onset. These findings emphasize the potential of combination therapy for improved migraine management.A review by Alorfi reviewed drugs tested in completed phase IV clinical trials for fibromyalgia.Analyzing 1,263 trials (121 related to fibromyalgia), they identified 10 meeting inclusion criteria.Investigated drugs targeting primary pain and cognitive-emotional pathways included milnacipran, duloxetine, pregabalin, tramadol-acetaminophen, and armodafinil. Despite these trials, current pharmacological treatments remain of limited effectiveness, emphasizing the need for alternative therapeutic strategies.Liu et al. conducted a Mendelian randomization analysis to explore the causal link between mood instability and chronic low back pain. Their findings demonstrated significant associations, with inverse variance weighting revealing odds ratios above 3.0, reinforcing the role of emotional dysregulation in chronic pain susceptibility.The issue is concluded with a study by Lopez-Cordoba et al. that investigated spinal α2adrenoceptor subtypes in nociception. Their results indicated that α2A-adrenoceptor activation contributes to antinociception in acute and tonic pain, while α2C-adrenoceptors may be pronociceptive under tonic nociceptive conditions, possibly by inhibiting GABAergic transmission.These findings highlight spinal adrenergic systems as potential therapeutic targets.Collectively, these studies underscore the multifaceted nature of chronic pain, integrating neuropathic pain, migraine, fibromyalgia, and low back pain with cognitive and emotional processing. Key brain regions-including the amygdala, VTA, mPFC, and ACC-alongside neurotransmitter-receptor systems such as CGRP-R, D2/D3, μOR, and α2-adrenoceptors, play paramount roles in pain perception, mood regulation, and cognitive function. Advances in understanding these mechanisms may facilitate targeted therapies addressing both sensory and affective pain components. Furthermore, pharmacological innovations, including monoclonal antibodies, botulinum toxin, and novel neuromodulators, hold promise for treatment-resistant conditions. A multidisciplinary approach targeting brain, spinal, and neurochemical systems, could offer more effective and comprehensive strategies for managing chronic pain and its associated cognitive and emotional dysfunctions.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,061
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,314
Écart entre enseignants0,302 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2025
Routes d'admission1
Résumé présentoui

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