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Enregistrement W4386957841 · doi:10.3389/fimmu.2023.1295751

Editorial: The role of immune response in overnutrition-induced metabolic syndrome

2023· editorial· en· W4386957841 sur OpenAlexaff
Xiliang Du, Xinwei Li, Xudong Sun, Wanhai Qin

Notice bibliographique

RevueFrontiers in Immunology · 2023
Typeeditorial
Langueen
DomaineMedicine
ThématiqueAdipokines, Inflammation, and Metabolic Diseases
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésOvernutritionImmune systemImmunologyMedicineMetabolic syndromeInternal medicineEndocrinologyDiabetes mellitusObesity

Résumé

récupéré en direct d'OpenAlex

1IntroductionThe unhealthy state of metabolic disorder caused by long-term overnutrition is the driving force of metabolic syndrome (Mets) characterized by insulin resistance, hypertension and dyslipidaemia, etc (1). Mets also is considered as a chronic state of low-grade inflammatory state marked by elevated circulating proinflammatory cytokines. The excessive production of proinflammatory cytokines has been linked to an increased risk of obesity, type 2 diabetes, fatty liver, and cardiovascular disease (2,3). Of note, metabolites from food, dietary ingredients, and natural products can regulate immune response and manipulate inflammatory state. Hence, it is meaningful to identify the mechanisms of overnutrition-induced Mets and explore inflammatory signaling pathways and mediators during the development of Mets, as well as to find potential strategy to treat low-grade chronic inflammation of Mets. Numerous scholars have directed their attention towards this topic and have acquired interesting discoveries. Within the research topic “The Role of Immune Response in Overnutrition-induced Metabolic Syndrome”, four recent studies investigated the underlying mechanism, diagnostic biomarkers and treatment of diseases linked to Mets. Alzheimer’s disease (AD) has an association with Mets. Clinical and epidemiological evidence indicates that Mets clusters promote the development of AD through various mechanisms. Identifying biomarkers is essential for diagnosing and treating many diseases. However, our understanding of the shared diagnosis and genes associated with both MS and AD is limited. Li et al. obtained eight common diagnostic genes in AD and Mets via the machine learning algorithm. The immune filtration analysis showed that four genes are highly expressed in different immune cell subpopulations. The common mechanism of AD and metabolic syndrome may involve pathways associated with glucose metabolism. Furthermore, the impact of glucose metabolism on AD patients could potentially be mediated by NK cells and B cells. The single-cell sequencing analysis suggested that SNRPG may act as a key gene related to glucose metabolism in AD patients. This study provides insights for the diagnosis and treatment of AD and Mets.Atherosclerosis (AS) is a complex disease with multiple causes. One of the factors contributing to AS is metabolic disorder (Mets). Researchers have investigated the potential therapeutic effects of Trichosanthes kirilowii and Allium macrostemon in managing AS-related diseases. However, the exact underlying mechanism is still not fully understood. Abnormal DNA methylation can also contribute to the development of AS. In a study conducted by Jia et al. a combined approach of MC-seq and RNA-seq was employed to investigate the effects of Gualou-xiebai herb pair (GXHP) treatment on foam cell models induced by ox-LDL treatment in RAW264.7 cells. The results suggested that GXHP appeared to reverse changes in gene expression by modulating abnormal hypermethylation and hypomethylation, resulting in reduced protein levels related to the PI3K-Akt signaling pathway in foam cells. This study has delineated the mechanism of action of GXPH as a novel methylation reagent in AS. Furthermore, it has provided novel insights into the exploration of disease mechanisms mediated by Mets.Mets is also linked to a higher risk of gout. It was generally believed that the inflammatory response only occurred in the urate deposition stage of gouty arthritis. While the involvement of the NLRP3/IL-1b inflammatory signaling pathway has been confirmed in gout arthritis, its contribution to the overall development of gout remains uncertain. In the work by Wu et al. in the pathological progression of gout, the upregulation of Xanthine oxidase expression facilitates uric acid production, disrupts oxidative stress equilibrium, generates a substantial quantity of reactive oxygen species, triggers the activation of NLRP3 inflammatory corpuscles, and induces the release of IL-1b in the quail gout model induced by over-nutrition. Meanwhile, they successfully obtained primary synovial fibroblasts in quail, thereby facilitating future investigations. This study holds significant reference value for the research and treatment of gout induced by Mets resulting from overnutrition.Serotonin has been demonstrated to exacerbate diet-induced obesity, insulin resistance, and non-alcoholic fatty liver disease in mice. It also affects the recruitment and function of white blood cells during inflammation. The study conducted by Hoch et al. elucidated that the absence of serotonin transporter in a knockout mouse model exacerbates obesity related inflammation. The inflammatory response in adipose tissue is attributed to elevated recruitment of leukocytes into obese visceral adipose tissue. This consequently exacerbates dysfunction of adipose tissue, disrupts systemic glucose regulation, and leads to liver steatosis. This study provides valuable information in the investigation of diseases related to metabolic syndrome and the selection of therapeutic medications. Collectively, these data, ideas and findings described in this series of articles pave the way for further research in the topic

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,013
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,016
Score d'incertitude au seuil0,054

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,013
Méta-épidémiologie (sens strict)0,0040,001
Méta-épidémiologie (sens large)0,0040,003
Bibliométrie0,0030,001
Études des sciences et des technologies0,0020,002
Communication savante0,0040,005
Science ouverte0,0040,001
Intégrité de la recherche0,0100,014
Charge utile insuffisante (le modèle a refusé de juger)0,0160,011

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 Opus0,006
Tête enseignante GPT0,248
Écart entre enseignants0,242 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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