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Record W4411354565 · doi:10.1021/acsabm.5c00865

Emerging Technologies and Solutions for Chronic Wound Care and Diagnosis

2025· editorial· en· W4411354565 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACS Applied Bio Materials · 2025
Typeeditorial
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsChronic woundIntensive care medicineWound careMedicineBusinessSurgeryWound healing

Abstract

fetched live from 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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.281
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.283
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it