Contact allergy caused by acrylates in nail cosmetics: A pilot study from Greece.

BACKGROUND: The growing popularity of nail techniques based on acrylates has led to a higher frequency of sensitization in both nail technicians and users. OBJECTIVES: The study aimed to assess cases of allergic contact dermatitis (ACD) caused by acrylates in individuals with occupational or non-occupational exposure to nail techniques. METHODS: A preliminary study was conducted on 30 patients with ACD caused by acrylates in nail techniques, who were patch tested from September 2022 to March 2023 at the First Department of Dermatology and Venereology of Andreas Syggros Hospital, Athens, Greece. RESULTS: Thirty female patients with ACD to acrylates were documented (15 users and 15 nail technicians and users). The most common allergens were: 2-hydroxyethyl methacrylate (HEMA), 2-hydroxypropyl methacrylate (HPMA) and ethyleneglycol dimethacrylate (EGDMA), which tested positive in all 30 patients (100.0%). Twenty patients (66.7%) had been exposed to dental procedures involving acrylates, before the onset of ACD. Nail technicians exhibited extensive skin lesions, 40.0% experienced ACD within the first year of work and 13.3% during their professional practice. Three of them (20.0%) had to discontinue their work. CONCLUSION: Acrylates have been identified as potent allergens, necessitating the implementation of safety measures for the use of these chemicals in nail techniques.

Detecting Skin Reactions in Epicutaneous Patch Testing with Deep Learning: An Evaluation of Pre-Processing and Modality Performance.

Epicutaneous patch testing is a well-established diagnostic method for identifying substances that may cause Allergic Contact Dermatitis (ACD), a common skin condition caused by exposure to environmental allergens. While the patch test remains the gold standard for identifying allergens, it is prone to observer bias and consumes valuable human resources. Deep learning models can be employed to address this challenge. In this study, we collected a dataset of 1579 multi-modal skin images from 200 patients using the Antera 3D® camera. We then investigated the feasibility of using a deep learning classifier for automating the identification of the allergens causing ACD. We propose a deep learning approach that utilizes a context-retaining pre-processing technique to improve the accuracy of the classifier. In addition, we find promise in the combination of the color image and false-color map of hemoglobin concentration to improve diagnostic accuracy. Our results showed that this approach can potentially achieve more than 86% recall and 94% specificity in identifying skin reactions, and contribute to faster and more accurate diagnosis while reducing clinician workload.

A Retrospective Analysis to Investigate Contact Sensitization in Greek Population Using Classic and Machine Learning Techniques.

Allergic contact dermatitis (ACD) is an inflammatory reaction affecting all age groups and both sexes. ACD is characterized by a delayed-type hypersensitivity reaction IV caused by skin contact with haptens. Chronic exposure typically leads to a decrease in erythema accompanied by lichenification (thickening and hardening of the skin) and persistent itching. The current study aims to investigate the patterns of contact sensitization in the Greek population using patch test data analysis. Patch test data from 240 patients (120 Males/120 Females) with allergic contact dermatitis were collected at the Laboratory for Patch Testing, National Reference Center for Occupational Dermatoses "Andreas Syggros" Hospital in Athens Greece. The contact allergic reactions were caused by ethylenediamine dihydrochloride 1%, thimerosal 0.5%, and methyldibromo-glutaronitrile 0.1% from the European baseline series of allergens; information was also collected for ICDRG evaluation, an extended MOAHLFA index and patient-reported outcomes (daily routine questionnaire). The chi-square test for independence and Spearman's rank were used to evaluate the association and correlation, respectively, between patient characteristics and ACD-related factors. Multiple correspondence analysis (MCA), which is a data analysis approach, was used to find and depict underlying structures in the data collection for nominal categorical data. Statistically significant associations were found between the following pairs of characteristics: eczema triggers and gender and eczema triggers and hand dermatitis. The results from MCA showed that there is correlation between allergic contact dermatitis onset, allergens, and demographic variables.

Ulvan-Based Nanofibrous Patches Enhance Wound Healing of Skin Trauma Resulting from Cryosurgical Treatment of Keloids.

Keloids are skin fibroproliferative disorders, resulting from abnormal healing of deep cutaneous injuries. Cryosurgery, the most common treatment for keloids, causes skin traumas. Even though the clinical practice of cryosurgery has increased, effective wound healing therapy is still lacking. In this investigation, nonwoven nanofibrous patches composed of ulvan, a marine sulfated polysaccharide exhibiting anti-inflammatory and antioxidant activities, and polyethylene oxide (PEO) were fabricated through electrospinning and characterized. Their wound healing efficacy on skin traumas resulting from cryosurgical treatment of keloids was clinically tested and evaluated in comparison to a reference product. Twenty-four volunteer patients undergoing cryosurgery as a treatment of keloids were selected to apply either the ulvan/PEO patch or the reference product for 21 days. The ulvan/PEO patch, 21 days after cryosurgery, showed significant wound healing, elimination of skin inflammation, restoration of biophysical parameters similar to normal values and significant decrease in haemoglobin concentration, skin texture and volume, while no discomfort or adverse reaction was observed. In contrast, the reference product showed inferior performance in all evaluated parameters. The designed ulvan/PEO patch represents the first wound dressing to effectively heal skin trauma after cryosurgical treatment of keloids.

Management of Acute Radiodermatitis in Non-Melanoma Skin Cancer Patients Using Electrospun Nanofibrous Patches Loaded with Pinus halepensis Bark Extract.

Acute radiodermatitis is the most common side effect in non-melanoma skin cancer patients undergoing radiotherapy. Nonetheless, despite the ongoing progress of clinical trials, no effective regimen has been found yet. In this study, a non-woven patch, comprised of electrospun polymeric micro/nanofibers loaded with an aqueous extract of Pinus halepensis bark (PHBE), was fabricated and clinically tested for its efficacy to prevent radiodermatitis. The bioactivity of the PHBE patch was evaluated in comparison with a medical cream indicated for acute radiodermatitis. Twelve volunteer patients were selected and randomly assigned to two groups, applying either the PHBE patch or the reference cream daily. Evaluation of radiation-induced skin reactions was performed during the radiotherapy period and 1 month afterwards according to the Radiation Therapy Oncology Group (RTOG) grading scale, photo-documentation, patient-reported outcomes (Visual Analog Scale, questionnaire), biophysical measurements (hydration, transepidermal water loss, erythema, melanin), and image analysis. In contrast with the reference product, the PHBE patch showed significant anti-inflammatory activity and restored most skin parameters to normal levels 1 month after completion of radiation therapy. No adverse event was reported, indicating that the application of the PHBE patch can be considered as a safe medical device for prophylactic radiodermatitis treatment.

Urticaria from the Neurodermatological Perspective: A Temporal Analysis of Urticaria and Cognition.

Chronic spontaneous urticaria (CSU, or CU) is a disease that significantly affects the quality of life of patients. The connection between the cognitive state of an individual and dermatological diseases has been previously reported, and it is known, although not thoroughly investigated, that there is a cognitive and quality of life relation to dermal pathologies. Urticaria is a chronic disease that requires a specialized approach to diagnosis and treatment but also a holistic approach with respect to the consideration of both the pathophysiology of the disease and the cognition status of the patient. The present study aims at analyzing CU score and cognitive indexes with respect to time, as a time series and their subsequent interactions. We have attempted to model the investigated time series in order to unravel possible causative relationships between cognitive/quality of life factors and urticaria. One hundred and eleven patients (29 males/82 females) admitted to our department were diagnosed with CU. CU was estimated on UAS7 score basis, which was used in order to define disease severity. Indexes used for assessing the cognitive and quality of life of patients' status included the Urticaria Control Test (UCT) and Dermatology Life Quality Index (DLQI). Significant correlations were found between UAS7 score and the UCT and DLQI scores, respectively. Interestingly, each score time series was modelled by different sets of equations, indicating the unique effect each one has on the disease, as well as that each score probably is manifested by a different pathophysiological mechanism.