Genome-wide Association Study of Susceptibility Loci for Self-Reported Atopic Dermatitis and Allergic Rhinitis in the Korean Population.

BACKGROUND: Allergic diseases include atopic dermatitis (AD) and allergic rhinitis (AR), which are chronic, relapsing inflammatory disorders of the skin or mucosa that usually accompany immunoglobulin E-mediated immune responses. They are complex, multifactorial diseases with an etiology involving interactions between genetic and environmental factors. OBJECTIVE: We performed a genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with allergic diseases in the Korean population. METHODS: A total of 8,840 samples were obtained from the Korean Association Resource Consortium dataset of the Korean Genome and Epidemiology Study Ansan-Anseong cohort. The allergic disease phenotype was determined based on self-reported physician diagnoses. After quality control, 8,823 subjects with 877,242 variants remained for the final analysis. The GWAS was performed using logistic regression analysis in an additive model adjusted for age and sex. RESULTS: A total of 636 patients with allergic disease and 8,176 controls were analyzed. Three SNPs were associated with allergic disease at a level of genome-wide suggestive significance (p<1.0×10-5) in the Korean population: rs7275360, located in neural cell adhesion molecule 2; rs698195; and rs3750552, located in family with sequence similarity 189, member A2. These polymorphisms were on chromosomes 21q21.1, 7q31.1, and 9q21.12, respectively. CONCLUSION: We identified 3 novel SNPs significantly associated with allergic diseases in the Korean population. Further research is required to confirm the association between these novel SNPs and allergic disease in the Korean population and in other ethnicities.

Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants.

Background: Scalp-related symptoms such as dandruff and itching are common with diverse underlying etiologies. We previously proposed a novel classification and scoring system for scalp conditions, called the scalp photographic index (SPI); it grades five scalp features using trichoscopic images with good reliability. However, it requires trained evaluators.Aim: To develop artificial intelligence (AI) algorithms for assessment of scalp conditions and to assess the feasibility of AI-based recommendations on personalized scalp cosmetics.Methods: Using EfficientNet, convolutional neural network (CNN) models (SPI-AI) ofeach scalp feature were established. 101,027 magnified scalp images graded according to the SPI scoring were used for training, validation, and testing the model Adults with scalp discomfort were prescribed shampoos and scalp serums personalized according to their SPI-AI-defined scalp types. Using the SPI, the scalp conditions were evaluated at baseline and at weeks 4, 8, and 12 of treatment.Results: The accuracies of the SPI-AI for dryness, oiliness, erythema, folliculitis, and dandruff were 91.3%, 90.5%, 89.6%, 87.3%, and 95.2%, respectively. Overall, 100 individuals completed the 4-week study; 43 of these participated in an extension study until week 12. The total SPI score decreased from 32.70 ± 7.40 at baseline to 15.97 ± 4.68 at week 4 (p < 0.001). The efficacy was maintained throughout 12 weeks.Conclusions: SPI-AI accurately assessed the scalp condition. AI-based prescription of tailored scalp cosmetics could significantly improve scalp health.

Generation of a Melanoma and Nevus Data Set From Unstandardized Clinical Photographs on the Internet.

Importance: Artificial intelligence (AI) training for diagnosing dermatologic images requires large amounts of clean data. Dermatologic images have different compositions, and many are inaccessible due to privacy concerns, which hinder the development of AI. Objective: To build a training data set for discriminative and generative AI from unstandardized internet images of melanoma and nevus. Design, Setting, and Participants: In this diagnostic study, a total of 5619 (CAN5600 data set) and 2006 (CAN2000 data set; a manually revised subset of CAN5600) cropped lesion images of either melanoma or nevus were semiautomatically annotated from approximately 500 000 photographs on the internet using convolutional neural networks (CNNs), region-based CNNs, and large mask inpainting. For unsupervised pretraining, 132 673 possible lesions (LESION130k data set) were also created with diversity by collecting images from 18 482 websites in approximately 80 countries. A total of 5000 synthetic images (GAN5000 data set) were generated using the generative adversarial network (StyleGAN2-ADA; training, CAN2000 data set; pretraining, LESION130k data set). Main Outcomes and Measures: The area under the receiver operating characteristic curve (AUROC) for determining malignant neoplasms was analyzed. In each test, 1 of the 7 preexisting public data sets (total of 2312 images; including Edinburgh, an SNU subset, Asan test, Waterloo, 7-point criteria evaluation, PAD-UFES-20, and MED-NODE) was used as the test data set. Subsequently, a comparative study was conducted between the performance of the EfficientNet Lite0 CNN on the proposed data set and that trained on the remaining 6 preexisting data sets. Results: The EfficientNet Lite0 CNN trained on the annotated or synthetic images achieved higher or equivalent mean (SD) AUROCs to the EfficientNet Lite0 trained using the pathologically confirmed public data sets, including CAN5600 (0.874 [0.042]; P = .02), CAN2000 (0.848 [0.027]; P = .08), and GAN5000 (0.838 [0.040]; P = .31 [Wilcoxon signed rank test]) and the preexisting data sets combined (0.809 [0.063]) by the benefits of increased size of the training data set. Conclusions and Relevance: The synthetic data set in this diagnostic study was created using various AI technologies from internet images. A neural network trained on the created data set (CAN5600) performed better than the same network trained on preexisting data sets combined. Both the annotated (CAN5600 and LESION130k) and synthetic (GAN5000) data sets could be shared for AI training and consensus between physicians.

Pigmented contact dermatitis and hair dyes: A retrospective case-control multicentre study in Korea.

BACKGROUND: Pigmented contact dermatitis (PCD), a rare variant of non-eczematous contact dermatitis, is clinically characterized by sudden-onset brown or grey pigmentation on the face and neck. It is hypothesized to be caused by repeated contact with low levels of allergens. OBJECTIVES: This study evaluated the risk of using hair dyes in patients with PCD in Korea. METHODS: A total of 1033 PCD patients and 1366 controls from 31 university hospitals were retrospectively recruited. We collected and analysed the data from the patient group, diagnosed through typical clinical findings of PCD and the control group, which comprised age/sex-matched patients who visited the participating hospitals with pre-existing skin diseases other than current allergic disease or PCD. RESULTS: Melasma and photosensitivity were significantly more common in the control group, and a history of contact dermatitis was more common in the PCD group. There were significantly more Fitzpatrick skin type V participants in the PCD group than in the control group. There was no significant difference in sunscreen use between the groups. Using dermatologic medical history, Fitzpatrick skin type and sunscreen use as covariates, we showed that hair dye use carried a higher PCD risk (odds ratio [OR] before adjustment: 2.06, confidence interval [CI]: 1.60-2.65; OR after adjustment: 2.74, CI: 1.88-4.00). Moreover, henna users had a higher risk of PCD (OR before adjustment: 5.51, CI: 4.07-7.47; OR after adjustment: 7.02, CI: 4.59-10.74), indicating a significant increase in the risk of PCD with henna dye use. Contact dermatitis history was more prevalent in henna users than in those using other hair dyes in the PCD group (17.23% vs. 11.55%). CONCLUSION: Hair dye use is a risk factor for PCD. The risk significantly increased when henna hair dye was used by those with a history of contact dermatitis.

Needleless laser injector versus needle injection for skin enhancement and rejuvenation effect of dermal filler.

BACKGROUND AND OBJECTIVES: A needleless laser-induced microjet injector is a novel transdermal drug delivery system that can rapidly inject a very small and precise drug dose into the skin with minimal pain and downtime. In this study, we aimed to compare the laser-induced microjet injection versus needle injection of polylactic acid/hyaluronic acid filler for skin enhancement and rejuvenation. PATIENTS AND METHODS: A 24-week prospective, single-center, assessor-blinded, randomized, split-face study was conducted. The enrolled patients underwent one treatment session of dermal filler injection using a laser-induced microjet injector on one half of the face or a traditional needle injection on the other half of the face. Evaluation was conducted at baseline before treatment and at 4, 12, and 24 weeks after treatment. RESULTS: A single treatment of filler injection with a laser-induced microjet injector resulted in similar improvements in skin hydration and elasticity as a single treatment of filler injection by using manual needle injection, with reduced pain, side effects, and decreased treatment time. CONCLUSIONS: Laser-induced microjet injector enabled not only the application of a controlled dose and filler depth but also even distribution, improved clinical efficacy, reduced pain and side effects, and sufficient time for clinicians to perform treatment.

A Randomized Split-Face Study of Photodynamic Therapy With St. John's Wort and Indole-3-Acetic Acid for the Treatment of Acne.

BACKGROUND: St. John's wort (SJW) contains hypericin, a powerful photosensitizer with antimicrobial and anti-inflammatory activities. OBJECTIVE: To compare the efficacy and safety of SJW-photodynamic therapy (PDT) with that of indole-3-acetic acid (IAA)-PDT for the treatment of acne and investigate the skin rejuvenating effects of SJW-PDT. MATERIALS AND METHODS: In vitro experiments were conducted to examine the generation of reactive oxygen species and the antimicrobial effects of SJW-PDT. In the prospective, double-blind, split-face, randomized study, 31 patients with facial acne were treated with SJW or IAA with simultaneous illumination of red light and green light. RESULTS: SJW produces free radicals with visible light irradiation, and the growth of Cutibacterium acnes and Staphylococcus aureus is significantly suppressed. One week after the last treatment, the acne lesion counts were significantly decreased in both groups (56.5% reduction in SJW, p < .001 vs 57.0% in IAA, p < .001). Significant reductions in sebum secretion, erythema index, roughness, and wrinkles were observed in both groups after the treatment. No side effects were observed. CONCLUSION: SJW-PDT is a simple, safe, and effective treatment option for acne that is also beneficial for skin rejuvenation.

Efficacy and Safety of the Micro-insulated Needle Radiofrequency Device for Reduction of Submental Fat.

BACKGROUND: Recently, it has been reported that a micro-insulated needle radiofrequency (RF) system is effective at achieving subcutaneous fat reduction; however, no study has yet applied this technique to reduce submental fat. OBJECTIVE: To evaluate the efficacy and safety of a fractional RF device with a micro-insulated needle to reduce submental fat. MATERIALS AND METHODS: In this prospective, single-blinded, pre-post comparative study, 24 adults with excess submental fat were treated once using a micro-insulated needle RF device. Outcomes included efficacy (submental fat rating by an independent investigator, fat volume quantified with a 3-dimensional camera, and patient satisfaction), assessed 1 and 2 months after the procedure, and safety (adverse events), assessed throughout the study. RESULTS: The patients' Physician-Assisted Submental Fat Rating Scale score significantly decreased after 1 month and further decreased after 2 months. The average volume of submental fat was significantly decreased after 2 months (20.44 ± 5.53 cc to 16.41 ± 4.58 cc, p < .001). Patient satisfaction was high. Transient and mild local skin reactions without long-term sequelae were observed in 4 patients. CONCLUSION: The micro-insulated needle RF device is beneficial for the reduction of submental fat and has tolerable safety profiles. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05517824.

Development of a new classification and scoring system for scalp conditions: Scalp Photographic Index (SPI).

BACKGROUND AND OBJECTIVES: There has been no validated tool for objectively quantifying the overall condition and characteristics of the scalp. This study aimed to establish and validate a new classification and scoring system for evaluating scalp conditions. METHODS: The Scalp Photographic Index (SPI) using a trichoscope grades five features of scalp conditions (dryness, oiliness, erythema, folliculitis, and dandruff) on a score of 0-3. To evaluate the validity of SPI, SPI grading was performed by three experts on the scalps of 100 subjects along with a dermatologist's assessment of the scalps and a scalp-related symptom survey. For reliability assessment, 20 healthcare providers performed SPI grading for the 95 selected photographs of the scalp. RESULTS: SPI grading and the dermatologist's scalp assessment showed good correlations for all five scalp features. Warmth showed a significant correlation with all features of SPI and the subjects' perception of a scalp pimple had a significant positive correlation with the folliculitis feature. SPI grading demonstrated good reliability with excellent internal consistency (Cronbach's α = 0.90) and strong inter- and intra-rater reliability (Kendall's W = 0.84, ICC(3,1)=0.94). CONCLUSIONS: SPI is an objective, reproducible, and validated numeric system for classifying and scoring scalp conditions.

Practical Training Approaches for Discordant Atopic Dermatitis Severity Datasets: Merging Methods With Soft-Label and Train-Set Pruning.

Objective assessment of atopic dermatitis (AD) is essential for choosing proper management strategies. This study investigated the performance of convolutional neural networks (CNN) models in grading the severity of AD. Five board-certified dermatologists independently evaluated the severity of 9,192 AD images. The severity of AD was evaluated based on an Investigator's Global Assessment (IGA) and six signs of AD. For CNN training, we applied three distinct approaches: 1) ensemble vs. integration 2) hard-label vs. soft-label and 3) train-set pruning. For the IGA prediction, the two best models were chosen based on the macro-averaged AUROC and F-1 score. The ensemble-soft-label-pruning model was chosen based on AUROC 0.943, 0.927 for the internal and external validation set respectively, and integration-soft-label-whole dataset model was chosen based on the F1-score 0.750, 0.721 for the internal and external validation set respectively. CNN models trained by multi-evaluator dataset outperformed the models by an individual evaluator dataset, and they performed better to the dataset in which the assessment of dermatologists was concordant. In conclusion, CNN models for AD could be improved by labeled dataset from multiple evaluators, merging methods with soft-label and train-set pruning.

Early Postoperative Injections of Polydeoxyribonucleotide Prevent Hypertrophic Scarring After Thyroidectomy: A Randomized Controlled Trial.

Objective: Polydeoxyribonucleotide (PDRN) is known to enhance wound healing, but there has been no clinical trial investigating the effect of PDRN on scar prevention in surgical wounds. This study aimed to evaluate the efficacy of PDRN administration in preventing postoperative scars. Approach: In this randomized controlled trial (NCT05149118), 44 patients who underwent open thyroidectomy were randomly assigned to the PDRN treatment or untreated control group. Only patients in the treatment group received two consecutive injections of PDRN 1 and 2 days after surgery. The modified Vancouver Scar Scale (mVSS), patients' subjective symptoms, erythema index (EI), melanin index (MI), and scar height were assessed 3 months after surgery. Results: Patients in the treatment group had lower mVSS scores (1.619 ± 1.244 vs. 2.500 ± 1.540, respectively; p = 0.059) and a significantly lower vascularity subscore (0.476 ± 0.512 vs. 0.900 ± 0.447, respectively; p = 0.010) than those in the control group at the 3-month follow-up. Compared with the control group, the level of subjective symptoms, EI, and scar height were all significantly lowered in the PDRN injection group. No specific side effects related to PDRN injection were observed. Innovation: This is the first clinical study that demonstrated that PDRN injections rapidly decreased postsurgical wound erythema and as a result, significantly reduced both excessive scar formation and accompanying symptoms. Conclusion: Early postoperative injection of PDRN is an effective and safe treatment to prevent hypertrophic scars and improve scar outcomes.

The degradation of performance of a state-of-the-art skin image classifier when applied to patient-driven internet search.

Model Dermatology ( https://modelderm.com ; Build2021) is a publicly testable neural network that can classify 184 skin disorders. We aimed to investigate whether our algorithm can classify clinical images of an Internet community along with tertiary care center datasets. Consecutive images from an Internet skin cancer community ('RD' dataset, 1,282 images posted between 25 January 2020 to 30 July 2021; https://reddit.com/r/melanoma ) were analyzed retrospectively, along with hospital datasets (Edinburgh dataset, 1,300 images; SNU dataset, 2,101 images; TeleDerm dataset, 340 consecutive images). The algorithm's performance was equivalent to that of dermatologists in the curated clinical datasets (Edinburgh and SNU datasets). However, its performance deteriorated in the RD and TeleDerm datasets because of insufficient image quality and the presence of out-of-distribution disorders, respectively. For the RD dataset, the algorithm's Top-1/3 accuracy (39.2%/67.2%) and AUC (0.800) were equivalent to that of general physicians (36.8%/52.9%). It was more accurate than that of the laypersons using random Internet searches (19.2%/24.4%). The Top-1/3 accuracy was affected by inadequate image quality (adequate = 43.2%/71.3% versus inadequate = 32.9%/60.8%), whereas participant performance did not deteriorate (adequate = 35.8%/52.7% vs. inadequate = 38.4%/53.3%). In this report, the algorithm performance was significantly affected by the change of the intended settings, which implies that AI algorithms at dermatologist-level, in-distribution setting, may not be able to show the same level of performance in with out-of-distribution settings.

Fibroblasts Close a Void in Free Space by a Purse-String Mechanism.

The mechanism by which stromal cells fill voids in injured tissue remains a fundamental question in regenerative medicine. While it is well-established that fibroblasts fill voids by depositing extracellular matrix (ECM) proteins as they migrate toward the wound site, little is known about their ability to adopt an epithelial-like purse-string behavior. To investigate fibroblast behavior during gap closure, we created an artificial wound with a large void space. We discovered that fibroblasts could form a free-standing bridge over deep microvoids, closing the void via purse-string contraction, a mechanism previously thought to be unique to epithelial wound closure. The findings also revealed that myosin II mediated contractility and intercellular adherent junctions were required for the closure of the fibroblast gap in our fabricated three-dimensional artificial wound. To fulfill their repair function under the specific microenvironmental conditions of wounds, fibroblasts appeared to acquire the structural features of epithelial cells, namely, contractile actin bundles that span over multiple cells along the boundary. These findings shed light on a novel mechanism by which stromal cells bridge the 3D gap during physiological processes such as morphogenesis and wound healing.

Basal cell carcinoma of the scalp shows distinct features from the face in Asians.

Basal cell carcinoma (BCC) affecting different sites has been reported to have different clinicopathological features. In previous studies, the scalp was commonly classified to the head and neck region. However, the scalp has distinct characteristics from those of other parts of the skin. We retrospectively reviewed the medical records of patients who underwent surgical treatment for BCC. A total of 734 lesions were examined, and 13.2% originated from the scalp. The nodular type was the most common histologic subtype; however, the proportion of the superficial type was significantly higher than that of facial BCC (p < 0.001). Compared with facial BCC, younger age (p = 0.046) and larger tumor size (p < 0.001) were observed in scalp BCC. These characteristics were similar to those of truncal BCC in that they demonstrated a higher proportion of the superficial type (p < 0.001), younger age (p = 0.001), and larger tumor diameter (p < 0.001) compared with BCC in the head and neck region. Scalp BCC and truncal BCC were not significantly different in terms of age (p = 0.052) and tumor size (p = 0.230). In conclusion, despite the anatomical proximity, features of scalp BCC were similar to those of truncal lesions compared with facial lesions. Scalp BCC might be a separate entity from facial BCC.

Augmenting the accuracy of trainee doctors in diagnosing skin lesions suspected of skin neoplasms in a real-world setting: A prospective controlled before-and-after study.

BACKGROUND: Although deep neural networks have shown promising results in the diagnosis of skin cancer, a prospective evaluation in a real-world setting could confirm these results. This study aimed to evaluate whether an algorithm (http://b2019.modelderm.com) improves the accuracy of nondermatologists in diagnosing skin neoplasms. METHODS: A total of 285 cases (random series) with skin neoplasms suspected of malignancy by either physicians or patients were recruited in two tertiary care centers located in South Korea. An artificial intelligence (AI) group (144 cases, mean [SD] age, 57.0 [17.7] years; 62 [43.1%] men) was diagnosed via routine examination with photographic review and assistance by the algorithm, whereas the control group (141 cases, mean [SD] age, 61.0 [15.3] years; 52 [36.9%] men) was diagnosed only via routine examination with a photographic review. The accuracy of the nondermatologists before and after the interventions was compared. RESULTS: Among the AI group, the accuracy of the first impression (Top-1 accuracy; 58.3%) after the assistance of AI was higher than that before the assistance (46.5%, P = .008). The number of differential diagnoses of the participants increased from 1.9 ± 0.5 to 2.2 ± 0.6 after the assistance (P < .001). In the control group, the difference in the Top-1 accuracy between before and after reviewing photographs was not significant (before, 46.1%; after, 51.8%; P = .19), and the number of differential diagnoses did not significantly increase (before, 2.0 ± 0.4; after, 2.1 ± 0.5; P = .57). CONCLUSIONS: In real-world settings, AI augmented the diagnostic accuracy of trainee doctors. The limitation of this study is that the algorithm was tested only for Asians recruited from a single region. Additional international randomized controlled trials involving various ethnicities are required.

Clinical Implication of the Regional Thickness of the Lower Facial Skin, Superficial Fat, and Superficial Musculoaponeurotic System on High-Intensity Focused Ultrasound Treatment.

BACKGROUND: Knowledge of the topographic thickness of the skin and soft tissues is necessary when performing a high-intensity focused ultrasound (HIFU) procedure. Thermal tissue injury to the superficial musculoaponeurotic system (SMAS) or deeper can injure the facial nerve and its branches. OBJECTIVE: To demonstrate the topographic thickness of the lower facial skin, superficial fat, and SMAS. MATERIALS AND METHODS: The ultrasound data of 200 healthy patients who underwent lower facial rejuvenation were retrospectively reviewed. RESULTS: The mean age was 41.1 ± 13.7 years (range, 19-76 years). The jowl had thinner skin, thicker superficial fat, and deeper superficial and deep margins of the SMAS than the preauricle or lower cheek. The thickness of the superficial fat decreased with age, especially on the preauricle, lower cheek, and jowl. Women had thicker superficial fat than men on the preauricle and lower cheek. The superficial and deep margins of the SMAS were located more superficially in old and male patients with a slim facial figure than in young and female patients with a chubby facial figure. CONCLUSION: The present findings provide anatomical information regarding the superficial fat and SMAS, which is useful in determining the focal penetration depth of HIFU treatment for lower face rejuvenation.