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Enregistrement W4411354565 · doi:10.1021/acsabm.5c00865

Emerging Technologies and Solutions for Chronic Wound Care and Diagnosis

2025· editorial· en· W4411354565 sur OpenAlex
Simon Matoori, Elisabeth Engel

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Notice bibliographique

RevueACS Applied Bio Materials · 2025
Typeeditorial
Langueen
DomaineMedicine
ThématiqueDiabetic Foot Ulcer Assessment and Management
Établissements canadiensUniversité de Montréal
Organismes subventionnairesnon disponible
Mots-clésChronic woundIntensive care medicineWound careMedicineBusinessSurgeryWound healing

Résumé

récupéré en direct d'OpenAlex

RecommendationsW ounds are common injuries that can significantly impact quality of life, especially when healing is delayed. [1][2]][3] When a wound does not progress through the normal stages of healing�inflammation, repair, and remodeling�it may become chronic.Chronic wounds fail to heal within an expected time frame and vary widely in cause, size, location, and severity.Conditions like diabetes, venous insufficiency, and prolonged pressure are common contributors. [4][5]5][6] In the U.S., chronic wounds affect millions and pose a growing burden due to aging populations and rising obesity rates.Clinically, chronic wounds are typically managed through regular debridement and the application of various wound dressings. 1,7Traditional dressings�such as gauze, hydrogels, foams, and films�support healing by maintaining moisture, allowing gas exchange, and protecting against infection. 1,7,8ome incorporate antimicrobial or debriding agents. 1,7More advanced options, including bioengineered skin substitutes, offer structural support and growth factor delivery but are costly and reserved for specialized care. 1,7Despite the wide range of available dressings, choosing the most appropriate option remains challenging due to limited high-quality comparative evidence and reliance on clinical judgment. 1Furthermore, the classification of chronic wounds follows a macroscopic clinical assessment. 9In light of advances in the pathophysiologic understanding of chronic wounds, there has been growing interest in the identification of new biomarkers and the development of new molecular sensors for improved wound characterization and molecular staging, treatment selection, and assessment of treatment response. [10][11]1][12] An emerging approach utilizes the body's innate regenerative potential by directing endogenous stem cells or tissue-specific progenitor cells to the wound site, enhancing repair and tissue regeneration.This strategy focuses on designing instructive systems that precisely regulate the spatial and temporal delivery of essential signals, aligning with the biological mechanisms governing various events within the host microenvironment.By orchestrating these processes, this method seeks to optimize healing dynamics, offering a more biologically driven solution to chronic wound management. 13,14hronic wounds�whether arising from diabetes, vascular insufficiency, or epithelial trauma�remain a pervasive clinical challenge due to their multifactorial pathophysiology and resistance to standard therapies.This Special Issue, "Breakthrough Technologies in Diagnosis and Therapy of Chronic Wounds", of ACS Pharmacology & Translational Science and ACS Applied Bio Materials brings together a collection of pioneering contributions that redefine how we diagnose, understand, and therapeutically approach chronic wounds.In a perspective, Mahmoud et al. highlight the intricate roles signaling molecules play and underline that a thorough understanding of the dynamic balance between pro-and anti-inflammatory cytokines is essential for advancing wound healing therapies. 15In the early phases of healing, cytokines and chemokines are critical for initiating inflammation, clearing debris, and attracting growth factors.As healing progresses, anti-inflammatory cytokines support the transition to tissue repair.Mahmoud et al. call for more rigorous, nuanced research methods; to achieve reliable outcomes in woundhealing studies, it is essential to adopt holistic approaches that account for the interplay, timing, and regulation of cytokines� supported by precise sampling and evaluation techniques.Expanding the diagnostic and mechanistic landscape, Gould and Mahmoudi present a metabolomic investigation of DFU exudates using cutting-edge chromatographic and spectrometric techniques. 16Their findings reveal that key bioactive metabolites including betaine, lactic acid, carnitine, choline, creatine, and drugs, namely metformin, are overexpressed in wounds.These molecules are known to play a role in key wound healing processes such as ECM synthesis, angiogenesis, inflammation, and energy metabolism.Intriguingly, the presence of metformin suggests pharmacodynamic interactions that could influence wound healing.This study highlights not only the biochemical complexity of the wound environment but also opportunities for personalized metabolic targeting.Diabetic foot ulcers (DFUs) remain an under-addressed complication of diabetes, with limited therapeutic progress over the past decades.The only FDA-approved drug� becaplermin, a PDGF-based gel�offers modest benefits. 4In a perspective, Chang advocates for the selective inhibition of matrix metalloproteinase-9 (MMP-9) as a therapeutic

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
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 enseignants0,281
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,001
Intégrité de la recherche0,0010,000
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 Opus0,010
Tête enseignante GPT0,283
Écart entre enseignants0,273 · 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