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In recent years, research on plant disease detection has combined artificial intelligence, hyperspectral imaging, unmanned aerial vehicle remote sensing, and other technologies, promoting the transformation of pest and disease control in smart agriculture towards digitalization and artificial intelligence. This review systematically elaborates on the research status of non-destructive detection techniques used for plant disease identification and detection, mainly introducing the following two types of methods: spectral technology and imaging technology. It also elaborates, in detail, on the principles and application examples of each technology and summarizes the advantages and disadvantages of these technologies. This review clearly indicates that non-destructive detection techniques can achieve plant disease and pest detection quickly, accurately, and without damage. In the future, integrating multiple non-destructive detection technologies, developing portable detection devices, and combining more efficient data processing methods will become the core development directions of this field. Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

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25 pages, 2860 KiB

Open AccessReview

Multimodal Sensing-Enabled Large Language Models for Automated Emotional Regulation: A Review of Current Technologies, Opportunities, and Challenges

by Liangyue Yu, Yao Ge, Shuja Ansari, Muhammad Imran and Wasim Ahmad

Sensors 2025, 25(15), 4763; https://doi.org/10.3390/s25154763 (registering DOI) - 1 Aug 2025

Abstract

Emotion regulation is essential for mental health. However, many people ignore their own emotional regulation or are deterred by the high cost of psychological counseling, which poses significant challenges to making effective support widely available. This review systematically examines the convergence of multimodal sensing technologies and large language models (LLMs) for the development of Automated Emotional Regulation (AER) systems. The review draws upon a comprehensive analysis of the existing literature, encompassing research papers, technical reports, and relevant theoretical frameworks. Key findings indicate that multimodal sensing offers the potential for rich, contextualized data pertaining to emotional states, while LLMs provide improved capabilities for interpreting these inputs and generating nuanced, empathetic, and actionable regulatory responses. The integration of these technologies, including physiological sensors, behavioral tracking, and advanced LLM architectures, presents the improvement of application, moving AER beyond simpler, rule-based systems towards more adaptive, context-aware, and human-like interventions. Opportunities for personalized interventions, real-time support, and novel applications in mental healthcare and other domains are considerable. However, these prospects are counterbalanced by significant challenges and limitations. In summary, this review synthesizes current technological advancements, identifies substantial opportunities for innovation and application, and critically analyzes the multifaceted technical, ethical, and practical challenges inherent in this domain. It also concludes that while the integration of multimodal sensing and LLMs holds significant potential for AER, the field is nascent and requires concerted research efforts to realize its full capacity to enhance human well-being. Full article

(This article belongs to the Section Intelligent Sensors)

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31 pages, 711 KiB

Open AccessReview

Persistent Threats: A Comprehensive Review of Biofilm Formation, Control, and Economic Implications in Food Processing Environments

by Alexandra Ban-Cucerzan, Kálmán Imre, Adriana Morar, Adela Marcu, Ionela Hotea, Sebastian-Alexandru Popa, Răzvan-Tudor Pătrînjan, Iulia-Maria Bucur, Cristina Gașpar, Ana-Maria Plotuna and Sergiu-Constantin Ban

Microorganisms 2025, 13(8), 1805; https://doi.org/10.3390/microorganisms13081805 (registering DOI) - 1 Aug 2025

Abstract

Biofilms are structured microbial communities that pose significant challenges to food safety and quality within the food-processing industry. Their formation on equipment and surfaces enables persistent contamination, microbial resistance, and recurring outbreaks of foodborne illness. This review provides a comprehensive synthesis of current knowledge on biofilm formation mechanisms, genetic regulation, and the unique behavior of multi-species biofilms. The review evaluates modern detection and monitoring technologies, including PCR, biosensors, and advanced microscopy, and compares their effectiveness in industrial contexts. Real-world outbreak data and a global economic impact analysis underscore the urgency for more effective regulatory frameworks and sanitation innovations. The findings highlight the critical need for integrated, proactive biofilm management approaches to safeguard food safety, reduce public health risks, and minimize economic losses across global food sectors. Full article

(This article belongs to the Special Issue Pathogenic Biofilms: Physiology, Molecular Mechanisms and Counter Strategies)

19 pages, 2264 KiB

Open AccessArticle

Extramedullary Plasmacytomas of the Nasal Cavity: Case-Based Perspectives into Optimizing the Diagnostic Differentiation from Inflammatory Polyps

by Carmen Aurelia Mogoantă, Codruț Sarafoleanu, Andrei Osman, Irina Enache, Shirley Tarabichi, Constantin-Ioan Busuioc, Ilona Mihaela Liliac, Dan Iovanescu and Ionuţ Tănase

Medicina 2025, 61(8), 1406; https://doi.org/10.3390/medicina61081406 (registering DOI) - 1 Aug 2025

Abstract

Background and Objectives: Extramedullary plasmacytoma (EMP) is a rare monoclonal B-cell neoplasm that typically affects the head and neck region, with a predilection for the sinonasal tract. Clinical presentation is often nonspecific, leading to delayed diagnosis. This study aims to improve our understanding of sinonasal EMP by reviewing the recent literature and presenting a case series from our clinical experience. Materials and Methods: A systematic review of published cases of sinonasal EMP from 2000 to 2023 was conducted using the PubMed database, yielding 28 eligible cases. Additionally, we retrospectively analyzed three patients diagnosed and treated at our institutions. Inclusion criteria included histologically and immunohistochemically confirmed EMP without evidence of systemic multiple myeloma. Data on demographics, tumor location, symptoms, treatment, and outcomes were collected and analyzed descriptively. Results: Sinonasal EMP most commonly presented with unilateral nasal obstruction and epistaxis. Tumors were primarily located in the nasal cavity and paranasal sinuses, often extending beyond a single anatomical site. In the literature cohort, the most frequent treatment was combined surgery and radiotherapy (35.71%), followed by radiotherapy alone (17.86%). Recurrence was reported in 10.71% of cases, and 7.14% of patients died due to disease progression. All three patients in our case series underwent surgical excision; two received postoperative radiotherapy. No recurrences or progression to multiple myeloma were observed during follow-up (12–24 months). Conclusions: Sinonasal EMP is a rare but radiosensitive tumor with a favorable prognosis when treated with surgery and/or radiotherapy. Early diagnosis, histopathological confirmation, and exclusion of systemic disease are essential. Multidisciplinary management and long-term follow-up are critical due to the risk of recurrence and transformation into multiple myeloma. Full article

(This article belongs to the Special Issue Optimizing Outcomes in Head and Neck Surgery)

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27 pages, 6085 KiB

Open AccessArticle

Assessing Model Trade-Offs in Agricultural Remote Sensing: A Review of Machine Learning and Deep Learning Approaches Using Almond Crop Mapping

by Mashoukur Rahaman, Jane Southworth, Yixin Wen and David Keellings

Remote Sens. 2025, 17(15), 2670; https://doi.org/10.3390/rs17152670 (registering DOI) - 1 Aug 2025

Abstract

This study presents a comprehensive review and comparative analysis of traditional machine learning (ML) and deep learning (DL) models for land cover classification in agricultural remote sensing. We evaluate the reported successes, trade-offs, and performance metrics of ML and DL models across diverse agricultural contexts. Building on this foundation, we apply both model types to the specific case of almond crop field identification in California’s Central Valley using Landsat data. DL models, including U-Net, MANet, and DeepLabv3+, achieve high accuracy rates of 97.3% to 97.5%, yet our findings demonstrate that conventional ML models—such as Decision Tree, K-Nearest Neighbor, and Random Forest—can reach comparable accuracies of 96.6% to 96.8%. Importantly, the ML models were developed using data from a single year, while DL models required extensive training data spanning 2008 to 2022. Our results highlight that traditional ML models offer robust classification performance with substantially lower computational demands, making them especially valuable in resource-constrained settings. This paper underscores the need for a balanced approach in model selection—one that weighs accuracy alongside efficiency. The findings contribute actionable insights for agricultural land cover mapping and inform ongoing model development in the geospatial sciences. Full article

(This article belongs to the Special Issue Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods)

28 pages, 8521 KiB

Open AccessReview

Pile Integrity Testing Using Non-Destructive Testing Techniques and Artificial Intelligence: A Review

by Peiyun Qiu, Liang Yang, Yilong Xie, Xinghao Liu and Zaixian Chen

Appl. Sci. 2025, 15(15), 8580; https://doi.org/10.3390/app15158580 (registering DOI) - 1 Aug 2025

Abstract

As civil engineering projects grow increasingly complex, ensuring pile integrity is essential for pile bearing capacity and structural safety. Pile integrity testing (PIT) has long been a focal point for researchers and engineers. With the rapid development of industrial-level advancements and artificial intelligence technology, PIT methods have undergone significant technological advancements. This paper reviews traditional PIT techniques, including low-strain integrity testing and thermal integrity profiling. The review covers the principles, advantages, limitations, and recent developments of various testing techniques. Additionally, recent advances in artificial intelligence (AI) techniques, particularly in signal processing and data-driven recognition methods, are discussed. Finally, the advantages, limitations, and potential future research directions of existing methods are summarized. This paper aims to offer a systematic reference for researchers and engineers in PIT, synthesizing technical details of traditional methods and their AI-enabled advancements. Furthermore, it explores potential directions for integrating AI with PIT, with a focus on key challenges such as noisy signal interpretation and regulatory barriers in applications. Full article

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23 pages, 1139 KiB

Open AccessArticle

A Critical Appraisal of Off-Label Use and Repurposing of Statins for Non-Cardiovascular Indications: A Systematic Mini-Update and Regulatory Analysis

by Anna Artner, Irem Diler, Balázs Hankó, Szilvia Sebők and Romána Zelkó

J. Clin. Med. 2025, 14(15), 5436; https://doi.org/10.3390/jcm14155436 (registering DOI) - 1 Aug 2025

Abstract

Background: Statins exhibit pleiotropic anti-inflammatory, antioxidant, and immunomodulatory effects, suggesting their potential in non-cardiovascular conditions. However, evidence supporting their repurposing remains limited, and off-label prescribing policies vary globally. Objective: To systematically review evidence on statin repurposing in oncology and infectious diseases, and to assess Hungarian regulatory practices regarding off-label statin use. Methods: A systematic literature search (PubMed, Web of Science, Scopus, ScienceDirect; 2010–May 2025) was conducted using the terms “drug repositioning” OR “off-label prescription” AND “statin” NOT “cardiovascular,” following PRISMA guidelines. Hungarian off-label usage data from the NNGYK (2008–2025) were also analyzed. Results: Out of 205 publications, 12 met the inclusion criteria—75% were oncology-focused, and 25% focused on infectious diseases. Most were preclinical (58%); only 25% offered strong clinical evidence. Applications included hematologic malignancies, solid tumors, Cryptococcus neoformans, SARS-CoV-2, and dengue virus. Mechanisms involved mevalonate pathway inhibition and modulation of host immune responses. Hungarian data revealed five approved off-label statin uses—three dermatologic and two pediatric metabolic—supported by the literature and requiring post-treatment reporting. Conclusions: While preclinical findings are promising, clinical validation of off-label statin use remains limited. Statins should be continued in cancer patients with cardiovascular indications, but initiation for other purposes should be trial-based. Future directions include biomarker-based personalization, regulatory harmonization, and cost-effectiveness studies. Full article

(This article belongs to the Section Pharmacology)

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20 pages, 9174 KiB

Open AccessReview

Marine-Derived Collagen and Chitosan: Perspectives on Applications Using the Lens of UN SDGs and Blue Bioeconomy Strategies

by Mariana Almeida and Helena Vieira

Mar. Drugs 2025, 23(8), 318; https://doi.org/10.3390/md23080318 (registering DOI) - 1 Aug 2025

Abstract

Marine biomass, particularly from waste streams, by-products, underutilized, invasive, or potential cultivable marine species, offers a sustainable source of high-value biopolymers such as collagen and chitin. These macromolecules have gained significant attention due to their biocompatibility, biodegradability, functional versatility, and broad applicability across health, food, wellness, and environmental fields. This review highlights recent advances in the uses of marine-derived collagen and chitin/chitosan. In alignment with the United Nations Sustainable Development Goals (SDGs), we analyze how these applications contribute to sustainability, particularly in SDGs related to responsible consumption and production, good health and well-being, and life below water. Furthermore, we contextualize the advancement of product development using marine collagen and chitin/chitosan within the European Union’s Blue bioeconomy strategies, highlighting trends in scientific research and technological innovation through bibliometric and patent data. Finally, the review addresses challenges facing the development of robust value chains for these marine biopolymers, including collaboration, regulatory hurdles, supply-chain constraints, policy and financial support, education and training, and the need for integrated marine resource management. The paper concludes with recommendations for fostering innovation and sustainability in the valorization of these marine resources. Full article

(This article belongs to the Special Issue Innovative Biotechnology Processes for Marine By-Products: From Waste Stream to Value Stream)

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34 pages, 2929 KiB

Open AccessReview

Recent Advances in PET and Radioligand Therapy for Lung Cancer: FDG and FAP

by Eun Jeong Lee, Hyun Woo Chung, Young So, In Ae Kim, Hee Joung Kim and Kye Young Lee

Cancers 2025, 17(15), 2549; https://doi.org/10.3390/cancers17152549 (registering DOI) - 1 Aug 2025

Abstract

Lung cancer is one of the most common cancers and the leading cause of cancer-related death worldwide. Despite advancements, the overall survival rate for lung cancer remains between 10% and 20% in most countries. However, recent progress in diagnostic tools and therapeutic strategies has led to meaningful improvements in survival outcomes, highlighting the growing importance of personalized management based on accurate disease assessment. ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) has become essential in the management of lung cancer, serving as a key imaging modality for initial diagnosis, staging, treatment response assessment, and follow-up evaluation. Recent developments in radiomics and artificial intelligence (AI), including machine learning and deep learning, have revolutionized the analysis of complex imaging data, enhancing the diagnostic and predictive capabilities of FDG PET/CT in lung cancer. However, the limitations of FDG, including its low specificity for malignancy, have driven the development of novel oncologic radiotracers. One such target is fibroblast activation protein (FAP), a type II transmembrane glycoprotein that is overexpressed in activated cancer-associated fibroblasts within the tumor microenvironment of various epithelial cancers. As a result, FAP-targeted radiopharmaceuticals represent a novel theranostic approach, offering the potential to integrate PET imaging with radioligand therapy (RLT). In this review, we provide a comprehensive overview of FDG PET/CT in lung cancer, along with recent advances in AI. Additionally, we discuss FAP-targeted radiopharmaceuticals for PET imaging and their potential application in RLT for the personalized management of lung cancer. Full article

(This article belongs to the Special Issue Molecular PET Imaging in Cancer Metabolic Studies)

20 pages, 865 KiB

Open AccessReview

Barriers and Facilitators to Artificial Intelligence Implementation in Diabetes Management from Healthcare Workers’ Perspective: A Scoping Review

by Giovanni Cangelosi, Andrea Conti, Gabriele Caggianelli, Massimiliano Panella, Fabio Petrelli, Stefano Mancin, Matteo Ratti and Alice Masini

Medicina 2025, 61(8), 1403; https://doi.org/10.3390/medicina61081403 (registering DOI) - 1 Aug 2025

Abstract

Background and Objectives: Diabetes is a global public health challenge, with increasing prevalence worldwide. The implementation of artificial intelligence (AI) in the management of this condition offers potential benefits in improving healthcare outcomes. This study primarily investigates the barriers and facilitators perceived by healthcare professionals in the adoption of AI. Secondarily, by analyzing both quantitative and qualitative data collected, it aims to support the potential development of AI-based programs for diabetes management, with particular focus on a possible bottom-up approach. Materials and Methods: A scoping review was conducted following PRISMA-ScR guidelines for reporting and registered in the Open Science Framework (OSF) database. The study selection process was conducted in two phases—title/abstract screening and full-text review—independently by three researchers, with a fourth resolving conflicts. Data were extracted and assessed using Joanna Briggs Institute (JBI) tools. The included studies were synthesized narratively, combining both quantitative and qualitative analyses to ensure methodological rigor and contextual depth. Results: The adoption of AI tools in diabetes management is influenced by several barriers, including perceived unsatisfactory clinical performance, high costs, issues related to data security and decision-making transparency, as well as limited training among healthcare workers. Key facilitators include improved clinical efficiency, ease of use, time-saving, and organizational support, which contribute to broader acceptance of the technology. Conclusions: The active and continuous involvement of healthcare workers represents a valuable opportunity to develop more effective, reliable, and well-integrated AI solutions in clinical practice. Our findings emphasize the importance of a bottom-up approach and highlight how adequate training and organizational support can help overcome existing barriers, promoting sustainable and equitable innovation aligned with public health priorities. Full article

(This article belongs to the Special Issue Advances in Public Health and Healthcare Management for Chronic Care)

29 pages, 1477 KiB

Open AccessReview

Bioinformation and Monitoring Technology for Environmental DNA Analysis: A Review

by Hyo Jik Yoon, Joo Hyeong Seo, Seung Hoon Shin, Mohamed A. A. Abedlhamid and Seung Pil Pack

Biosensors 2025, 15(8), 494; https://doi.org/10.3390/bios15080494 (registering DOI) - 1 Aug 2025

Abstract

Environmental DNA (eDNA) analysis has emerged as a transformative tool in environmental monitoring, enabling non-invasive detection of species and microbial communities across diverse ecosystems. This study systematically reviews the role of bioinformation technology in eDNA analysis, focusing on methodologies and applications across air, soil, groundwater, sediment, and aquatic environments. Advances in molecular biology, high-throughput sequencing, bioinformatics tools, and field-deployable detection systems have significantly improved eDNA detection sensitivity, allowing for early identification of invasive species, monitoring ecosystem health, and tracking pollutant degradation processes. Airborne eDNA monitoring has demonstrated potential for assessing microbial shifts due to air pollution and tracking pathogen transmission. In terrestrial environments, eDNA facilitates soil and groundwater pollution assessments and enhances understanding of biodegradation processes. In aquatic ecosystems, eDNA serves as a powerful tool for biodiversity assessment, invasive species monitoring, and wastewater-based epidemiology. Despite its growing applicability, challenges remain, including DNA degradation, contamination risks, and standardization of sampling protocols. Future research should focus on integrating eDNA data with remote sensing, machine learning, and ecological modeling to enhance predictive environmental monitoring frameworks. As technological advancements continue, eDNA-based approaches are poised to revolutionize environmental assessment, conservation strategies, and public health surveillance. Full article

(This article belongs to the Section Environmental Biosensors and Biosensing)

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17 pages, 1907 KiB

Open AccessSystematic Review

Pilomatricoma in Syndromic Contexts: A Literature Review and a Report of a Case in Apert Syndrome

by Gianmarco Saponaro, Elisa De Paolis, Mattia Todaro, Francesca Azzuni, Giulio Gasparini, Antonio Bosso, Giuliano Ascani, Angelo Minucci and Alessandro Moro

Dermatopathology 2025, 12(3), 24; https://doi.org/10.3390/dermatopathology12030024 (registering DOI) - 1 Aug 2025

Abstract

Pilomatricomas are benign tumors originating from hair follicle matrix cells and represent the most common skin tumors in pediatric patients. Pilomatricomas may be associated with genetic syndromes such as myotonic dystrophy, familial adenomatous polyposis (FAP), Turner syndrome, Rubinstein–Taybi syndrome, Kabuki syndrome, and Sotos syndrome. This study reviews the literature on pilomatricomas occurring in syndromic contexts and presents a novel case linked to Apert syndrome. A systematic review was conducted using PubMed and Cochrane databases, focusing on case reports, case series, and reviews describing pilomatricomas associated with syndromes. A total of 1272 articles were initially screened; after removing duplicates and excluding articles without syndromic diagnoses or lacking sufficient data, 81 full-text articles were reviewed. Overall, 96 cases of pilomatricomas associated with genetic syndromes were identified. Reports of patients with Apert syndrome who do not develop pilomatricomas are absent in the literature. Pilomatricomas predominantly affect pediatric patients, with a slight female predominance, and are often the first manifestation of underlying genetic syndromes. Our study highlights previously unreported associations of pilomatricoma with Apert syndrome, providing molecular insights. This study contributes to understanding the clinical and molecular features of pilomatricomas in syndromic contexts and underscores the importance of genetic analysis for accurate diagnosis and management. Full article

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13 pages, 371 KiB

Open AccessReview

Dentistry in the Era of Artificial Intelligence: Medical Behavior and Clinical Responsibility

by Fabio Massimo Sciarra, Giovanni Caivano, Antonino Cacioppo, Pietro Messina, Enzo Maria Cumbo, Emanuele Di Vita and Giuseppe Alessandro Scardina

Prosthesis 2025, 7(4), 95; https://doi.org/10.3390/prosthesis7040095 (registering DOI) - 1 Aug 2025

Abstract

Objectives: Digitalization has revolutionized dentistry, introducing advanced technological tools that improve diagnostic accuracy and access to healthcare. This study aims to examine the effects of integrating digital technologies into the dental field, analyzing the associated benefits and risks, with particular paid attention to the therapeutic relationship and decision-making autonomy. Materials and Methods: A literature search was conducted in PubMed, Scopus, Web of Science, and Cochrane Library, complemented by Google Scholar for non-indexed studies. The selection criteria included peer-reviewed studies published in English between 2014 and 2024, focusing on digital dentistry, artificial intelligence, and medical ethics. This is a narrative review. Elements of PRISMA guidelines were applied to enhance transparency in reporting. Results: The analysis highlighted that although digital technologies and AI offer significant benefits, such as more accurate diagnoses and personalized treatments, there are associated risks, including the loss of empathy in the dentist–patient relationship, the risk of overdiagnosis, and the possibility of bias in the data. Conclusions: The balance between technological innovation and the centrality of the dentist is crucial. A human and ethical approach to digital medicine is essential to ensure that technologies improve patient care without compromising the therapeutic relationship. To preserve the quality of dental care, it is necessary to integrate digital technologies in a way that supports, rather than replaces, the therapeutic relationship. Full article

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32 pages, 1970 KiB

Open AccessReview

A Review of New Technologies in the Design and Application of Wind Turbine Generators

by Pawel Prajzendanc and Christian Kreischer

Energies 2025, 18(15), 4082; https://doi.org/10.3390/en18154082 (registering DOI) - 1 Aug 2025

Abstract

The growing global demand for electricity, driven by the development of electromobility, data centers, and smart technologies, necessitates innovative approaches to energy generation. Wind power, as a clean and renewable energy source, plays a pivotal role in the global transition towards low-carbon power systems. This paper presents a comprehensive review of generator technologies used in wind turbine applications, ranging from conventional synchronous and asynchronous machines to advanced concepts such as low-speed direct-drive (DD) generators, axial-flux topologies, and superconducting generators utilizing low-temperature superconductors (LTS) and high-temperature superconductors (HTS). The advantages and limitations of each design are discussed in the context of efficiency, weight, reliability, scalability, and suitability for offshore deployment. Special attention is given to HTS-based generator systems, which offer superior power density and reduced losses, along with challenges related to cryogenic cooling and materials engineering. Furthermore, the paper analyzes selected modern generator designs to provide references for enhancing the performance of grid-synchronized hybrid microgrids integrating solar PV, wind, battery energy storage, and HTS-enhanced generators. This review serves as a valuable resource for researchers and engineers developing next-generation wind energy technologies with improved efficiency and integration potential. Full article

(This article belongs to the Special Issue Advancements in Marine Renewable Energy and Hybridization Prospects)

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13 pages, 1189 KiB

Open AccessArticle

The Role of Biodegradable Temporizing Matrix in Paediatric Reconstructive Surgery

by Aikaterini Bini, Michael Ndukwe, Christina Lipede, Ramesh Vidyadharan, Yvonne Wilson and Andrea Jester

J. Clin. Med. 2025, 14(15), 5427; https://doi.org/10.3390/jcm14155427 (registering DOI) - 1 Aug 2025

Abstract

Introduction: Biodegradable Temporizing Matrix (BTM) is a new synthetic dermal substitute suitable for wound closure and tissue regeneration. The data in paediatric population remain limited. The study purpose is to review the indications for BTM application in paediatric patients; evaluate the short-term and long-term results, including complications and functional outcomes, as well as to share some unique observations regarding the use of BTM in paediatric population. Patients and Methods: Patients undergoing reconstructive surgery and BTM application during the last three years were included. Data collected included patient demographics, primary diagnosis, previous surgical management, post-operative complications and final outcomes. BTM was used in 32 patients. The indications varied including epidermolysis bullosa (n = 6), burns (n = 4), trauma (n = 7), infection (n = 4), ischemia or necrosis (n = 11). Results: The results were satisfying with acceptable aesthetic and functional outcomes. Complications included haematomaunderneath the BTM leading to BTM removal and re-application (n = 1), BTM infection (n = 1) and split-thickness skin graft failure on top of BTM requiring re-grafting (n = 2). Conclusions: BTM can be a good alternative to large skin grafts, locoregional flaps or even free flaps. The big advantages over other dermal substitutes or skin grafts are that BTM is less prone to infection and offers excellent scarring by preserving the normal skin architecture. Specifically in children, BTM might not require grafting, resulting in spontaneous healing with good scarring. In critically ill patients, BTM reduces the operation time and there is no donor site morbidity. BTM should be considered in the reconstructive ladder when discussing defect coverage options in children and young people. Full article

(This article belongs to the Special Issue Trends in Plastic and Reconstructive Surgery)

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