9. The Cellular and Molecular Impact of Adjacent Tissue Type on Breast Implant Capsule
Notice bibliographique
Résumé
Purpose: Implant based breast augmentation and breast reconstruction are two of the most commonly performed plastic surgery procedures. However, capsular contracture occurs in approximately 10% of cases and requires surgery to correct. Breast implants in contact with muscle are less susceptible to capsular contracture than breast implants in contact with gland tissue. This raises the possibility that tissue types differentially modulate capsular physiology. The purpose of this study was to investigate the differences in breast implant capsule at the cellular and molecular level, depending on adjacent tissue types. This may provide important information regarding the progression to capsular contracture and suggest surgical targets for capsulectomy to improve treatment outcomes. Methods: Capsule against each tissue type (skin, gland, pectoralis) in contact with the breast implant was collected from consenting patients undergoing revision breast implant surgery. Specimens were assessed histologically for capsular thickness and collagen organization. Capsular cell populations were measured by cells per high powered field for immunohistochemically stained specimens with CD68 (total macrophages), iNOS (M1 macrophages), CD206 (M2 macrophages), CD3 (total T cells), vimentin (fibroblasts) and α-smooth muscle actin (myofibroblasts). Expression of cytokines (IL-1β, IL-6), extracellular matrix (Col1, Col3) and growth factor TGF-β were measured with RT-PCR. Statistical analyses included one-way ANOVAs and unpaired t-tests. Results: 15 capsule samples were collected of each adjacent tissue type. Gland capsule (531.0μm) was significantly thinner than skin (746.4μm) or pectoralis capsule (878.7μm)(p <.05). Collagen organization of gland capsule was significantly more abnormal and immature compared to skin capsule. Gland capsule had significantly increased numbers of T cells compared to skin capsule (skin = 12.1, gland = 54.3; p <.05) and significantly decreased numbers of total macrophages (skin = 18.2; gland = 15.2, pec = 28.1; p <.05) and M1 macrophages (skin = 4.22, gland = 0.1, pec = 3.1; p <.05). All groups had similar numbers of myofibroblasts (skin = 101.3, gland = 97.6, pec = 74.5; p=.55) and fibroblasts (skin = 71.8, gland = 108.0, pec = 110.9; p =.41). Gland capsule expressed significantly higher levels TGF-β (skin =.71, gland =.95, pec =.62; p =.05) and Col3 (skin =.52, gland =.76, pec =.61; p <.02). All groups expressed similar levels of IL-1β, IL-6 and Col1 (p >.05). Conclusion: Our data here shows that specific tissues surrounding breast implants uniquely impact the composition of capsule. Gland capsule had indications of excessive ECM remodelling evidenced by immature collagen organization and increased expression of collagen 3. The increased expression of TGF-β may also be related to the increased susceptibility of subglandular breast implants to capsular contracture. A potential explanation of the ECM activity in gland capsule may be related to high CD4+ T cell numbers which suggest a chronic adaptive inflammatory response. Overall, breast implant capsule that developed adjacent to gland tissue was found to have increased ECM remodeling, TGF-β expression and CD4+ T cells in comparison capsule adjacent to other tissue types. This suggests a potential pathophysiological basis for the increased susceptibility of subglandular breast implants to capsular contracture.
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 distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».