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Bioengineering
Special Issues
Research on Skin Diseases and Difficult Wounds
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Research on Skin Diseases and Difficult Wounds

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Regenerative Engineering".

Deadline for manuscript submissions: closed (20 October 2023) | Viewed by 3558

Special Issue Editor

Dr. Agata Janowska

E-Mail Website
Guest Editor
Department of Dermatology, University of Pisa, 56126 Pisa, Italy
Interests: wound healing; atypical wounds; skin cancers
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wound healing is a complex process, and dermatologic diseases are often associated with it. The constant improvements in diagnostic and therapeutic procedures, together with the increase in life expectancy, result in a higher frequency of patients suffering from chronic cutaneous diseases. The persistence of a chronic disease, despite treatment with standard therapies, requires a more specific diagnostic investigation. Diagnosis involves performing a history, clinical examination, and additional tests. A skin biopsy is frequently used to confirm the condition of a patient with an unclear diagnosis, environment as well as severity influence monitoring, and treatment frequency. New therapies for chronic wounds and dermatologic diseases have led to improvements in  management and in the quality of care provided by medical and nursing staff. This Special Issue of Bioengineering will focus on research on skin diseases and difficult wounds.

Dr. Agata Janowska
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • atypical ulcers
  • chronic ulcers
  • dermatologic diseases
  • new treatments

Published Papers (2 papers)

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Research

26 pages, 4135 KiB  
Article
Enhancing Skin Cancer Detection and Classification in Dermoscopic Images through Concatenated MobileNetV2 and Xception Models
by Roseline Oluwaseun Ogundokun, Aiman Li, Ronke Seyi Babatunde, Chinecherem Umezuruike, Peter O. Sadiku, AbdulRahman Tosho Abdulahi and Akinbowale Nathaniel Babatunde
Bioengineering 2023, 10(8), 979; https://doi.org/10.3390/bioengineering10080979 - 19 Aug 2023
Cited by 3 | Viewed by 1506
Abstract
One of the most promising research initiatives in the healthcare field is focused on the rising incidence of skin cancer worldwide and improving early discovery methods for the disease. The most significant factor in the fatalities caused by skin cancer is the late [...] Read more.
One of the most promising research initiatives in the healthcare field is focused on the rising incidence of skin cancer worldwide and improving early discovery methods for the disease. The most significant factor in the fatalities caused by skin cancer is the late identification of the disease. The likelihood of human survival may be significantly improved by performing an early diagnosis followed by appropriate therapy. It is not a simple process to extract the elements from the photographs of the tumors that may be used for the prospective identification of skin cancer. Several deep learning models are widely used to extract efficient features for a skin cancer diagnosis; nevertheless, the literature demonstrates that there is still room for additional improvements in various performance metrics. This study proposes a hybrid deep convolutional neural network architecture for identifying skin cancer by adding two main heuristics. These include Xception and MobileNetV2 models. Data augmentation was introduced to balance the dataset, and the transfer learning technique was utilized to resolve the challenges of the absence of labeled datasets. It has been detected that the suggested method of employing Xception in conjunction with MobileNetV2 attains the most excellent performance, particularly concerning the dataset that was evaluated: specifically, it produced 97.56% accuracy, 97.00% area under the curve, 100% sensitivity, 93.33% precision, 96.55% F1 score, and 0.0370 false favorable rates. This research has implications for clinical practice and public health, offering a valuable tool for dermatologists and healthcare professionals in their fight against skin cancer. Full article
(This article belongs to the Special Issue Research on Skin Diseases and Difficult Wounds)
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16 pages, 2857 KiB  
Article
Non-Invasive Monitoring of Cutaneous Wound Healing in Non-Diabetic and Diabetic Model of Adult Zebrafish Using OCT Angiography
by Jaeyoung Kim, Suhyun Kim and Woo June Choi
Bioengineering 2023, 10(5), 538; https://doi.org/10.3390/bioengineering10050538 - 27 Apr 2023
Cited by 3 | Viewed by 1700
Abstract
A diabetic wound presents a severe risk of infections and other complications because of its slow healing. Evaluating the pathophysiology during wound healing is imperative for wound care, necessitating a proper diabetic wound model and assay for monitoring. The adult zebrafish is a [...] Read more.
A diabetic wound presents a severe risk of infections and other complications because of its slow healing. Evaluating the pathophysiology during wound healing is imperative for wound care, necessitating a proper diabetic wound model and assay for monitoring. The adult zebrafish is a rapid and robust model for studying human cutaneous wound healing because of its fecundity and high similarities to human wound repair. OCTA as an assay can provide three-dimensional (3D) imaging of the tissue structure and vasculature in the epidermis, enabling monitoring of the pathophysiologic alterations in the zebrafish skin wound. We present a longitudinal study for assessing the cutaneous wound healing of the diabetic adult zebrafish model using OCTA, which is of importance for the diabetes research using the alternative animal models. We used non-diabetic (n = 9) and type 1 diabetes mellitus (DM) adult zebrafish models (n = 9). The full-thickness wound was generated on the fish skin, and the wound healing was monitored with OCTA for 15 days. The OCTA results demonstrated significant differences between diabetic and non-diabetic wound healing, involving delayed tissue remodeling and impaired angiogenesis for the diabetic wound, leading to slow wound recovery. The adult zebrafish model and OCTA technique may benefit long-term metabolic disease studies using zebrafish for drug development. Full article
(This article belongs to the Special Issue Research on Skin Diseases and Difficult Wounds)
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