Editorial: New players on the monoaminergic field: relevance to the mental disorders
Notice bibliographique
Résumé
It is well established that monoamines, such as serotonin (5-HT), noradrenaline, and dopamine, are fundamental in emotions and mood regulation. They also play a key role in the pathophysiology and treatment of mood disorders, such as unipolar and bipolar depression, as well as anxiety disorders, such as generalized anxiety, obsessive-compulsive, panic, and post-traumatic stress disorders [1]. We may underline three factors that are of critical importance for the proper understanding of the role of monoamines in mood disorders. The first one is the autoregulatory mechanism within the monoaminergic circuits [2]. The second one is the multiple crossinteraction between different monoamines [3]. The third factor is the crosstalk between monoamines and other bioactive molecules influencing mood regulation and mental functions in general. Examples of particularly important bioactive molecules are amino acid neurotransmitters, trace amines (biological amines biochemically related to the "classical" monoamines, but present in the brain in trace concentrations, such as tyramine, octopamine, and tryptamine), corticosteroids, adenosine, endogenous opioids, and cannabinoids (Fig 1).While the auto-and cross-regulatory mechanisms of the central monoaminergic systems have been extensively studied in the last decades, the crosstalk between monoamines and specific other biomolecules involved in mood regulation received lesser attention. This collection of articles was prepared in order to diminish this gap in knowledge and to stimulate future research in this direction.The task was completed thanks to the international team of researchers, coming from different parts of the world (Asia, America, Europe) and employment sectors (universities, public hospitals and research centers, and industrial enterprises). These researchers contributed their outstanding articles addressing the abovementioned points.Sha Zhao and colleagues from the Qingdao University, Qingdao, China, provided a review article on endocannabinoid-monoamine interactions, learning, and memory. Elad Lerer and co-authors from the Hadassah Medical Center, Jerusalem, Israel, contributed original research on the neurochemical mechanisms underlying putative beneficial effect of psychedelics in mental disorders. Daniela Jezova with Eliyahu Dremencov and their co-authors from the Biomedical Research Center and Centre of Biosciences, Slovak Academy of Sciences, Bratislava, Slovakia, shared with us an original research article on functional interactions between monoamines, glutamate, and endogenous opioids, focusing on prenatal effect of the ligands of opioid receptors on monoaminergic and glutamatergic transmission. Stephen Daniels and co-authors from the Institute of Mental Health Research, University of Ottawa, Ottawa, Canada, prepared an original research paper on glutamate-monoamine interactions and their role in the rapid antidepressant effect of ketamine. Hurmat Malik and co-contributors from the COMSATS University Islamabad, Islamabad, Pakistan, shared with us the results of their research on the interactions between monoamines, adenosine, microelements and steroids, with a practical focus on the putative anxiolytic and antidepressant-like effects of a natural element, diosgenin. Karolina Kolaczynska and Legend to the Figure Figure 1: Functional interactions between monoamines and other signaling biomolecules. VTA DA, ventral tegmental area dopamine neuron, LC NA, locus coeruleus noradrenaline neuron, TMN HA, tuberomammillary nucleus histamine neuron, DRN 5-HT, dorsal raphe nucleus serotonin (5-HT) neuron, ARN BEN, arcuate nucleus β-endorphin neuron, PFC GLU, prefrontal cortex glutamate neuron, A2A, adenosine-2A receptor, D2, dopamine-2 receptor, α1/2-alpha-1/2 adrenoceptor, H1/3histamine-1/3 receptor, 5-HT1A, serotonin-1A receptor, DOR-δ-opioid receptor, GR, glucocorticoid receptor, NMDA, N-methyl-D-aspartate glutamate receptor, CB1, cannabinoid-1 receptor, TAAR1, trace amine associated receptor 1, CS, corticosteroids, EC, endocannabinoids, +, stimulatory effect, -, inhibitory effect. According to [3; 4; 5; 6; 7; 8; 9].
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,009 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,030 | 0,018 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».