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Enregistrement W2028537409 · doi:10.1155/2012/785196

Signals Regulating Adhesion Dynamics

2012· article· en· W2028537409 sur OpenAlexaff
Donna J. Webb, Claire M. Brown, Kris A. DeMali

Notice bibliographique

RevueJournal of Signal Transduction · 2012
Typearticle
Langueen
DomaineMedicine
ThématiqueCell Adhesion Molecules Research
Établissements canadiensMcGill University
Organismes subventionnairesNational Institute of General Medical Sciences
Mots-clésMedicineDynamics (music)Adhesion

Résumé

récupéré en direct d'OpenAlex

Adhesions are sites of contact between cells (cell-cell) and between cells and the extracellular matrix (cell-ECM) that are essential for numerous biological processes such as embryogenesis, wound healing, and the immune response. They are composed of many different molecules including adhesion receptors, signaling proteins (e.g., kinases, phosphatases, and adaptor proteins), and structural proteins (e.g., actin-binding proteins) [1–3]. Adhesions are dynamic structures whose molecular composition and structure can undergo rapid changes to allow cells to respond to external signals [1, 4]. Indeed, this dynamic nature of adhesions within localized regions of cells is critical for many complex processes such as cell migration. For cell-ECM adhesions, their assembly is initiated by the binding of integrin adhesion receptors to the ECM. These new adhesions can either disassemble, allowing cells to migrate, or continue to mature by recruiting signaling and structural proteins to these sites. The dynamics and composition of adhesions are controlled by signaling networks that function to integrate molecular signals from outside and within cells. This special issue focuses on the molecular signals that regulate adhesion dynamics with an emphasis on cell-ECM adhesions. Integrins are transmembrane adhesion receptors that provide a functional link between the ECM and the actin cytoskeleton. Integrin engagement of the ECM serves to transduce signals to the interior of cells which regulate cell behavior. RGD-dependent integrins are a subgroup of adhesion receptors that specifically recognize the RGD motif, which is a three-amino-acid sequence (Arg-Gly-Asp) that is found in some ECM proteins. In this special issue, Y. D. Benoit et al. review recent findings regarding the importance of RGD-dependent integrins in epithelial cell homeostasis. Integrins also play important roles in blood clotting and wound healing by regulating platelet adhesion and aggregation. G. F. Guidetti and M. Torti discuss recent insights into the role of Rap1 in regulating platelet adhesion. Rap1 is a member of the Rap family of small GTPases and is a downstream effector of integrin signaling. A-Kinase-Anchoring Proteins (AKAP) are emerging as pivotal scaffolding proteins that bring together key signaling molecules to modulate cell migration. S. Akakura and I. H. Gelman provide insight into the regulation of AKAP12 and how it contributes to cell adhesion. Moreover, they discuss the scaffolding function of AKAP12 and its contribution to cell migration, maintenance of cytoskeletal architecture, cell proliferation, and cytokinesis. While integrin-containing matrix contacts were first identified in classic focal adhesions, they have subsequently been shown to exist in other structures including podosomes and invadopodia. Podosomes and invadopodia do not have the typical elongated shape of focal adhesions but form circular adhesive structures. Podosomes are found in phagocytic cells, while invadopodia are found in cancer cells, where as their name implies, they play a critical role in cancer cell invasion into the surrounding stroma. Focal adhesions, podosomes, and invadopodia share some of the same proteins, but they differ in their basic structure and function. P. P. Eleniste and A. Bruzzaniti compare and contrast the organization and function of focal adhesions, podosomes, and invadopodia. They highlight critical tyrosine kinases and signaling proteins that regulate the assembly and function of these adhesive structures. Cytotoxic necrotizing factors (CNF) are a class of autotransporter toxins that are made by uropathogenic E. coli (CNF1-3) and Y. pseudotuberculosis (CNFγ). CNF toxins deamidate and thus constitutively activate RhoA, Rac1, and Cdc42, which are critical regulators of adhesion dynamics. In this special issue, M. May et al. analyze the effects of CNF on cell-matrix adhesion. They show that CNF1 and CNFγ increase cell-matrix adhesion, resulting in reduced migration. They further indicate that the augmented cell-matrix adhesion is dependent on RhoA deamidation. Adherens junctions are cell-cell adhesion sites that are important for the establishment and maintenance of apico-basal polarity of epithelial cells. C. Bertocchi et al. give an overview of the kinases and phosphatases that regulate the phosphorylation of adherens junction proteins. In addition, they discuss the phosphorylation events that control the assembly and disassembly of adherens junctions. Overall, this special issue is a reflection of the diverse roles (e.g., epithelial cell homeostasis to the immune response to cancer) that adhesions play in biological processes and diseases. This issue provides an overview of the different types of adhesive structures, including focal adhesions, adherens junctions, and podosome as well as the molecular composition, regulation, and dynamics of these structures. The goal of this special issue is to provide the reader with an appreciation of the importance and function of adhesions and a synopsis of key signaling molecules that comprise adhesions. Donna J. Webb Claire M. Brown Kris A. DeMali

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)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,027
Score d'incertitude au seuil0,089

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0020,001
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0270,011

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 Opus0,036
Tête enseignante GPT0,317
Écart entre enseignants0,282 · 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'étudeThéorique ou conceptuel
Domainenon disponible
GenreSynthèse

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
Publié2012
Routes d'admission1
Résumé présentoui

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