Immunosupportive therapies in aging
Notice bibliographique
Résumé
Tamas Fülöp1, Anis Larbi2, Katsuiku Hirokawa3, Eugenio Mocchegiani4, Bruno Lesourd5, Stephen Castle6, Anders Wikby7, Claudio Franceschi8, Graham Pawelec21Research Center on Aging, Immunology Program, Geriatric Division, Faculty of Medicine, University of Sherbrooke, Quebec, Canada; 2Tübingen Ageing and Tumour Immunology Group, Center for Medical Research, University of Tübingen Medical School, Tübingen, Germany; 3Department of Pathology and Immunology Ageing and Developmental Sciences, Tokyo-Medical and Dental University Graduate School, Tokyo, Japan; 4Immunology Center, Section Nutrition, Immunity and Ageing, Research Department, Italian National Research Centres on Ageing, INRCA, Ancona, Italy; 5Hopital Universitaire de Clermont-Ferrand, Service Soins de Suite, Route de Châteaugay BP56, F-63118 Cebazat, France; 6Geriatric Research, Education and Clinical Center (GRECC), VA Greater Los Angeles Healthcare System and Multicampus Division of Geriatric and Gerontology, Department of Medicine, UCLA, Los Angeles, CA 90073, USA; 7School of Health Sciences, Jönköping University, Department of Natural Science and Biomedicine, Jönköping, Sweden; 8Italian National Research Center on Aging, Department of Experimental pathology, University of Bologna, Bologna, ItalyAbstract: The primary role of the immune system is to protect the organism against pathogens, but age-associated alterations to immunity increase the susceptibility of the elderly to infectious disease. The exact nature of these changes is still controversial, but the use of screening procedures, such as the SENIEUR protocol to exclude underlying illness, helped to better characterize the changes actually related to physiological aging rather than pathology. It is generally agreed that the most marked changes occur in the cellular immune response reflecting profound alterations in T cells. Much of this is due to thymic involution as well as changes in the proportions of T cell subpopulations resulting from antigen exposure, and altered T cell activation pathways. However, a body of data indicates that innate immune responses, including the critical bridge between innate and adaptive immunity, and antigen presenting capacity are not completely resistant to senescence processes. The consequences of all these alterations are an increased incidence of infections, as well as possibly cancers, autoimmune disorders, and chronic inflammatory diseases. The leading question is what, if anything, can we do to prevent these deleterious changes without dangerously dysregulating the precarious balance of productive immunity versus immunopathology? There are many potential new therapeutic means now available to modulate immunosenescence and many others are expected to be available shortly. One main problem in applying these experimental therapies is ethical: there is a common feeling that as ageing is not a disease; the elderly are not sick and therefore do not require adventurous therapies with unpredictable side-effects in mostly frail individuals. Animal models are not helpful in this context. In this chapter we will first briefly review what we think we know about human immunosenescence and its consequences for the health status of elderly individuals. We will then discuss possible interventions that might one day become applicable in an appropriate ethical environment.Keywords: immunosenescence, T cells, phagocytic cells, nutrition, vaccination, exercise, CMV, inflammaging, IRP, immunorestorative therapies
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».