MétaCan
Menu
Retour à la cohorte
Enregistrement W2064082832 · doi:10.1155/2014/920613

Cytokines and Diabetes Research

2014· editorial· en· W2064082832 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.

Notice bibliographique

RevueJournal of Diabetes Research · 2014
Typeeditorial
Langueen
DomaineMedicine
ThématiqueAdipokines, Inflammation, and Metabolic Diseases
Établissements canadiensLondon Health Sciences CentreWestern University
Organismes subventionnairesnon disponible
Mots-clésDiabetes mellitusMedicineInternal medicineEndocrinology

Résumé

récupéré en direct d'OpenAlex

In recent years, the role of the inflammatory system in the pathogenesis of diabetes has been increasingly investigated. Cytokines, a group of proteins that are expressed by several cell types, act as immune mediators and regulators. Depending on the period of pregnancy, a predominant inflammatory profile is defined by increased production of cytokines. Insulin resistance has been associated with abnormal secretion of proinflammatory cytokines such as tumor necrosis factor-α (TNF-α) and Interleukin-6 (IL-6) and decreased production of anti-inflammatory mediators such as IL-4 and IL-10. Despite some controversies regarding specific cytokine levels, type 2 diabetes mellitus (T2DM) is currently regarded as a chronic inflammatory disease, while type 1 diabetes (T1D) is considered to be a T-helper-(Th)-1 autoimmune disease. Extensive research in animals and in humans over the last decade has revealed important functions of cytokines in diabetes; adiponectin (APN) and leptin can decrease hepatic gluconeogenesis, resistin (REN) can increase hepatic gluconeogenesis and glycogenolysis, IL-6 can decrease glycogen synthesis, and TNF-α can decrease glucose uptake in liver. Both of them can block hepatic insulin signalling by interfection of insulin receptor signalling and insulin signal transduction. Thus, cytokines are involved in nearly every facet of immunity, inflammation, and development of diabetes. In this special issue, we have invited some papers hoping to shed light on some aspects of this very interesting field. We have collected 7 papers by scientists from 5 countries. In the submitted research papers, Y. Li et al. summarize recent findings regarding the relationship between adipocytokines and hepatic insulin resistance. Excessive adipose tissue may be detrimental partially through secretion of the following cytokines: TNF-α, IL-6, and resistin. In contrast, the presence of adipose tissues is vital in the prevention of hepatic insulin resistance via secretion of the following cytokines: leptin and adiponectin. While J. Su and colleagues review the relationship between the endoplasmic reticulum (ER) and autophagy, inflammation, and apoptosis in DM to better understand the molecular mechanisms of diabetes, the authors suggest that the ER is therefore an attractive potential therapeutic target, and maintaining or improving ER function appropriately may prevent diabetes. Z. Meng et al. concluded that ethanol causes glucose intolerance by increasing hepatic expression of 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) and glucocorticoid receptor (GR), which leads to increased expression of gluconeogenic and glycogenolytic enzymes. In the following papers, J. Liu et al. have shown that uncoupling proteins (UCPs) may affect the development of DM through decreasing mitochondrial membrane potential, increasing energy expenditure especially through glucose and lipid metabolisms, downregulating ROS generation, and gene polymorphisms. In a very interesting research paper, J. Vcelakova et al. have shown, that in T1D patients, important immune response-related pathways were involved. These important immune response-related processes largely included the induction of Th17 and Th22 responses, as well as cytoskeletal rearrangements, MHCII presentation, and the upregulation of CD4, TGF-beta, and STAT3. These findings potentially suggest that these processes could be utilised as predictive markers for the development of T1D or as molecular targets for the repression of specific immunocompetent cell populations for the treatment of diabetes. On the other hand, H. Meng and colleagues demonstrate that amyloid precursor protein 17 peptide (APP17 peptide) has a comprehensive therapeutic effect on diabetic encephalopathy, particularly through improving glycol metabolism. Finally, M. Cui et al. have shown that AMPK activation, which was represented by the level of p-AMPK, did not correlate with the improvement of metabolic conditions in diabetes mice, implying that AMPK activation may not participate in mediating the beneficial effects of chronic caloric restriction (CR) or exercise. However, the autophagy activity might be related to the improved metabolic conditions; thus autophagy may play a role in mediating the effects of chronic CR.

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.

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)0,016
score de la tête « metaresearch » (Gemma)0,038
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,577
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0160,038
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0030,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,005
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 Opus0,044
Tête enseignante GPT0,391
Écart entre enseignants0,347 · 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