Utilizing systems genetics to enhance understanding into molecular targets of skin cancer.

Despite progress made with immune checkpoint inhibitors and targeted therapies, skin cancer remains a significant public health concern in the United States. The intricacies of the disease, encompassing genetics, immune responses, and external factors, call for a comprehensive approach. Techniques in systems genetics, including transcriptional correlation analysis, functional pathway enrichment analysis, and protein-protein interaction network analysis, prove valuable in deciphering intricate molecular mechanisms and identifying potential diagnostic and therapeutic targets for skin cancer. Recent studies demonstrate the efficacy of these techniques in uncovering molecular processes and pinpointing diagnostic markers for various skin cancer types, highlighting the potential of systems genetics in advancing innovative therapies. While certain limitations exist, such as generalizability and contextualization of external factors, the ongoing progress in AI technologies provides hope in overcoming these challenges. By providing protocols and a practical example involving Braf, we aim to inspire early-career experimental dermatologists to adopt these tools and seamlessly integrate these techniques into their skin cancer research, positioning them at the forefront of innovative approaches in combating this devastating disease.

Artificial Intelligence for the Classification of Pigmented Skin Lesions in Populations with Skin of Color: A Systematic Review.

BACKGROUND: While skin cancers are less prevalent in people with skin of color, they are more often diagnosed at later stages and have a poorer prognosis. The use of artificial intelligence (AI) models can potentially improve early detection of skin cancers; however, the lack of skin color diversity in training datasets may only widen the pre-existing racial discrepancies in dermatology. OBJECTIVE: The aim of this study was to systematically review the technique, quality, accuracy, and implications of studies using AI models trained or tested in populations with skin of color for classification of pigmented skin lesions. METHODS: PubMed was used to identify any studies describing AI models for classification of pigmented skin lesions. Only studies that used training datasets with at least 10% of images from people with skin of color were eligible. Outcomes on study population, design of AI model, accuracy, and quality of the studies were reviewed. RESULTS: Twenty-two eligible articles were identified. The majority of studies were trained on datasets obtained from Chinese (7/22), Korean (5/22), and Japanese populations (3/22). Seven studies used diverse datasets containing Fitzpatrick skin type I-III in combination with at least 10% from black Americans, Native Americans, Pacific Islanders, or Fitzpatrick IV-VI. AI models producing binary outcomes (e.g., benign vs. malignant) reported an accuracy ranging from 70% to 99.7%. Accuracy of AI models reporting multiclass outcomes (e.g., specific lesion diagnosis) was lower, ranging from 43% to 93%. Reader studies, where dermatologists' classification is compared with AI model outcomes, reported similar accuracy in one study, higher AI accuracy in three studies, and higher clinician accuracy in two studies. A quality review revealed that dataset description and variety, benchmarking, public evaluation, and healthcare application were frequently not addressed. CONCLUSIONS: While this review provides promising evidence of accurate AI models in populations with skin of color, the majority of the studies reviewed were obtained from East Asian populations and therefore provide insufficient evidence to comment on the overall accuracy of AI models for darker skin types. Large discrepancies remain in the number of AI models developed in populations with skin of color (particularly Fitzpatrick type IV-VI) compared with those of largely European ancestry. A lack of publicly available datasets from diverse populations is likely a contributing factor, as is the inadequate reporting of patient-level metadata relating to skin color in training datasets.

Exploring the interactions of antihistamine with retinoic acid receptor beta (RARB) by molecular dynamics simulations and genome-wide meta-analysis.

Kaposi sarcoma (KS) is one of the most common AIDS-related malignant neoplasms, which can leave lesions on the skin among HIV patients. These lesions can be treated with 9-cis-retinoic acid (9-cis-RA), an endogenous ligand of retinoic acid receptors that has been FDA-approved for treatment of KS. However, topical application of 9-cis-RA can induce several unpleasant side effects, like headache, hyperlipidemia, and nausea. Hence, alternative therapeutics with less side effects are desirable. There are case reports associating over-the-counter antihistamine usage with regression of KS. Antihistamines competitively bind to H1 receptor and block the action of histamine, best known for being released in response to allergens. Furthermore, there are already dozens of antihistamines that are FDA-approved with less side effects than 9-cis-RA. This led our team to conduct a series of in-silico assays to determine whether antihistamines can activate retinoic acid receptors. First, we utilized high-throughput virtual screening and molecular dynamics simulations to model high-affinity interactions between antihistamines and retinoic acid receptor beta (RARß). We then performed systems genetics analysis to identify a genetic association between H1 receptor itself and molecular pathways involved in KS. Together, these findings advocate for exploration of antihistamines against KS, starting with our two promising hit compounds, bepotastine and hydroxyzine, for experimental validation study in the future.

Integrative Approaches to Sleep Management in Skin Disease: Systematic Review.

BACKGROUND: Dermatological conditions, especially when severe, can lead to sleep disturbances that affect a patient's quality of life. However, limited research exists on the efficacy of treatments for improving sleep parameters in skin conditions. OBJECTIVE: The objective was to perform a systematic review of the literature on dermatological conditions and the treatments available for improving sleep parameters. METHODS: A literature review was performed using the PubMed, Ovid MEDLINE, Embase, Cochrane, and ClinicalTrials.gov databases from 1945 to 2021. After filtering based on our exclusion criteria, studies were graded using the SORT (Strength of Recommendation Taxonomy) algorithm, and only those receiving a grade of "2" or better were included. RESULTS: In total, 25 treatment studies (n=11,025) assessing sleep parameters related to dermatological conditions were found. Dupilumab appeared to be the best-supported and most effective treatment for improving sleep in atopic dermatitis (AD) but had frequent adverse effects. Topical treatments for AD were mostly ineffective, but procedural treatments showed some promise. Treatments for other conditions appeared efficacious. CONCLUSIONS: The evaluation of sleep parameter changes in dermatological treatments is predominantly restricted to AD. Systemic interventions such as dupilumab and procedural interventions were the most efficacious. Sleep changes in other dermatoses were limited by a paucity of available studies. The inclusion of a sleep assessment component to a broader range of dermatological treatment studies is warranted.

Assessment of US Radiology Residency Program Websites in the COVID-19 Era.

OBJECTIVE: To provide an updated evaluation of radiology residency program websites in light of virtual interviewing during the COVID-19 pandemic and encourage programs to improve the quality of their online website presence. METHODS: We evaluated the websites of 197 US radiology residency programs between November and December 2021 for the presence or absence of 30 metrics. The metrics chosen are those considered important by applicants when choosing a program and have been used in other similar papers. RESULTS: Of the 197 programs, 192 (97.5%) had working websites. The average radiology residency website had 16 of 30 (54%) metrics listed on their websites. Five programs did not have accessible websites and were not included in the analysis. The most comprehensive website had 29 of 30 (97%) of metrics listed and the least comprehensive website had 2 of 30 (7%). There is a statistically significant difference in website comprehensiveness between top 20 and non-top 20 radiology program websites. CONCLUSION: Although radiology residency program websites have generally become more comprehensive over time, there is still room for improvement, especially in times of virtual interviews when residency applicants are becoming more and more reliant on program websites to gain essential information about a program. Some key areas to include are diversity and inclusion initiatives, resident wellness, applicant information, program benefits, and showcase of people in the program.

Outcomes of Onabotulinum Toxin A Treatment for Adductor Spasmodic Dysphonia and Laryngeal Tremor.

Importance: The relative outcomes of onabotulinum toxin A injections for treatment of adductor spasmodic dysphonia (ADSD), ADSD with lateral laryngeal tremor (ADSD+LT), and lateral LT without ADSD are unclear. Objective: To compare the outcomes of onabotulinum toxin A treatment on ADSD, ADSD+LT, and lateral LT without ADSD. Design, Setting, and Participants: A retrospective cohort study was conducted from January 1, 1990, to September 30, 2016, at a tertiary referral voice center. Participants included 817 patients treated with onabotulinum toxin A injections for diagnosis of ADSD, ADSD+LT, and lateral LT without ADSD. Exposure: Injection of onabotulinum toxin A into the thyroarytenoid/lateral cricoarytenoid muscle complex. Main Outcomes and Measures: Data from patient diaries were used to evaluate patient-perceived effectiveness of onabotulinum toxin A injection. Primary outcomes were (1) patient-reported good voice days (voice breaks or tremor minimized to patient satisfaction) and (2) percentage of injections in which maximal voice quality was reached (significant or complete reduction in vocal tremor or spasms during a treatment cycle). Multivariate analysis of variance tests compared differences in outcomes between groups. Subanalysis was performed to compare outcomes in patients with isolated LT with those who had mixed tremor (lateral with concomitant anterior-posterior and/or vertical components). Results: Of 817 patients treated with onabotulinum toxin A injections for laryngeal movement disorders, 548 patients (12 771 injection sessions) met inclusion criteria (ADSD: n = 328, ADSD+LT: n = 77, lateral LT without ADSD: n = 143). Of these, 408 (80.8%) were women; mean (SD) age was 57.2 (13.7) years. Among patients with tremor, those with isolated LT had better outcomes than those with mixed tremor. In adjusted analysis, good voice days in patients with ADSD, ADSD+LT, and lateral LT without ADSD were 81.1, 75.4, and 71.3 days, respectively (partial η2, 0.05; 95% CI, 0.01-0.09). The percentage of maximally beneficial injections was 88.1% for ADSD, 83.4% for ADSD+LT, and 70.4% for LT without ADSD (partial η2, 0.12; 95% CI, 0.06-0.17). Conclusions and Relevance: Onabotulinum toxin A injections into the thyroarytenoid/lateral cricoarytenoid muscle complex are an effective treatment for ADSD, ADSD+LT, and LT without ADSD; however, the greatest effectiveness was observed among patients with ADSD. Defining tremor directionality may help to prognosticate the effectiveness of onabotulinum toxin A injection among patients presenting with tremor components.