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Case Presentation: A patient with a known history of pustular psoriasis presented with sub-acute development of diffuse erythema and scaling of the skin with areas of exfoliation consistent with erythroderma.  She was ill appearing and required admission and aggressive treatment with steroid-impregnated wet dressings, topical emollients, analgesics and systemic immunosuppressants.Discussion: Erythroderma is a dermatologic emergency characterized by diffuse erythema and scaling spanning >90% of skin surfaces and is associated with a mortality rate as high as 64%.  It is initially a clinical diagnosis and needs to be recognized and aggressively treated expeditiously to improve chances of a good outcome.

Psoriasis, an immune-mediated inflammatory skin disorder characterized by a chronically relapsing-remitting course, continues to be primarily managed through topical therapy. While oral administration of tyrosine kinase 2 inhibitors (TYK2i) stands as an effective approach for psoriasis treatment, the potential efficacy of topical application of TYK2i remains unexplored. Herein, the carbomer/alginic acid hydrogel is embedded with borneol (BO) as a new topical carrier of TYK2i for achieving enhanced transdermal permeation and anti-psoriasis efficacy. The hydrogel system, i.e., TYK2i-BO-gel, exhibits significantly improved preventative and therapeutic effects in mice models of psoriasiform dermatitis, as evidenced by phenotypical images, psoriasis severity score index (PSI), histology, immunohistochemical staining, and PCR analysis. Remarkably, TYK2i-BO-gel outperforms conventional topical corticosteroid therapy by significantly preventing psoriatic lesion recurrence as measured by a nearly 50 % reduction in ear thickness changes (p

Psoriasis is a chronic, immune-mediated inflammatory skin disease associated with a polygenic mode of inheritance. There are few studies that explore the association of a psoriasis Polygenic Risk Score (PRS) with patient clinical characteristics, and to our knowledge there are no studies examining psoriasis PRS associations across different ethnicities. In this study, we used a multi-racial psoriasis cohort to investigate PRS associations with clinical phenotypes including age of onset, psoriatic arthritis, other comorbidities, psoriasis body location, psoriasis subtype, environmental triggers, and response to therapies. We collected patient data and Affymetrix genome-wide SNP data from a cohort of 607 psoriasis patients and calculated an 88-loci PRS (PRS-ALL), also partitioned between genetic loci within the HLA region (PRS-HLA; 11 SNPS) and loci outside the HLA region (PRS-NoHLA; 77 SNPS). We used t-test and logistic regression to analyze the association of PRS with clinical phenotypes. We found that PRS-HLA and PRS-noHLA had differing effects on psoriasis age of onset, psoriatic arthritis, psoriasis located on the ears, genitals, nails, soles of feet, skin folds, and palms, skin injury as an environmental trigger, cardiovascular comorbidities, and response to phototherapy. In some cases these PRS associations were ethnicity specific. Overall, these results show that the genetic basis for clinical manifestations of psoriasis are driven by distinct HLA and non-HLA effects, and that these PRS associations can be dependent on ethnicity.

PURPOSE OF REVIEW: Machine learning (ML), a subset of artificial intelligence (AI), has been vital in advancing tasks such as image classification and speech recognition. Its integration into clinical medicine, particularly dermatology, offers a significant leap in healthcare delivery. RECENT FINDINGS: This review examines the impact of ML on psoriasis-a condition heavily reliant on visual assessments for diagnosis and treatment. The review highlights five areas where ML is reshaping psoriasis care: diagnosis of psoriasis through clinical and dermoscopic images, skin severity quantification, psoriasis biomarker identification, precision medicine enhancement, and AI-driven education strategies. These advancements promise to improve patient outcomes, especially in regions lacking specialist care. However, the success of AI in dermatology hinges on dermatologists oversight to ensure that MLs potential is fully realized in patient care, preserving the essential human element in medicine. SUMMARY: This collaboration between AI and human expertise could define the future of dermatological treatments, making personalized care more accessible and precise.