This narrative review focuses on psoriasis, a chronic recurrent inflammatory skin disease with multisystem comorbidities that significantly impairs patients' quality of life. The recurrent nature of the disease often imposes substantial psychological burden, accompanied by anxiety, depression, and social avoidance behaviors. Precise dynamic assessment throughout the entire diagnostic and therapeutic cycle is crucial for improving patient prognosis. Artificial intelligence technology, with its powerful image recognition and data analysis capabilities, provides a novel technical pathway for dynamic assessment of psoriasis. This review comprehensively summarizes research progress of AI technology in whole-process assessment of psoriasis before, during, and after treatment, analyzing application characteristics and performance advantages of different AI models in auxiliary disease diagnosis, severity scoring, treatment regimen optimization, relapse risk prediction, comorbidity screening, and psychological status assessment. Furthermore, we examine the core challenges currently faced, including lack of data standardization, insufficient diversity of population and subtype-specific data, unresolved ethical and privacy protection concerns, and barriers to interdisciplinary clinical integration. AI models such as convolutional neural networks and deep learning can effectively improve the accuracy of psoriasis diagnosis and the objectivity of severity assessment, and also exhibit promising application potential in treatment regimen screening, therapeutic effect simulation, prognostic monitoring, and psychological burden identification. Moreover, multimodal fusion and cross-technology integration have emerged as important development directions. To address the existing challenges, future research should focus on advancing the construction of standardized and diverse data systems, fostering interdisciplinary expertise, developing an integrated AI model covering diagnosis, assessment, treatment, prognosis, and psychological status monitoring, and strengthening multicenter clinical validation and the establishment of ethical norms. This review demonstrates that the deep integration of AI technology with dynamic assessment of psoriasis can provide strong support for precise and individualized long-term disease management, and holds important clinical value for optimizing psoriasis diagnosis and treatment regimens, reducing the disease burden, and improving patients' mental health.
Objective: Psoriasis is a chronic inflammatory skin disease driven by dysregulated immune responses and keratinocyte activation. How topical disulfiram (DSF) ameliorates imiquimod-induced psoriatic dermatitis beyond pyroptosis inhibition remains unclear. This study aims to elucidate its cellular and molecular mechanisms and assess its multi‑target therapeutic potential. Methods: A murine model was established with petroleum jelly, imiquimod, and DSF treatment groups. Single-cell RNA sequencing of dorsal skin was performed to construct a cellular atlas. Bioinformatic analyses were conducted to identify key DSF-responsive populations. Findings were validated by flow cytometry, histology, and enzyme-linked immunosorbent assay. The role of Ly6C hi monocytes was evaluated using a selective C-C chemokine receptor type 2 (CCR2) inhibitor. Network pharmacology and molecular docking analyses were conducted to predict multi-target mechanisms. Results: Keratinocytes and myeloid cells were identified as central targets. DSF suppressed the expansion of a pathogenic keratinocyte subtype (Epd_DF2) and inhibited psoriasis-associated proinflammatory and metabolic pathways. DSF altered the functional activation state of Ly6C hi monocytes without affecting their abundance. In T cells, DSF attenuated IL-23/IL-17 axis activation, as reflected by reduced Il17a and Il17f expression and increased inhibitory signatures. CCR2 inhibition attenuated disease severity, reduced serum IL-17A levels, and significantly decreased Ly6C hi monocyte proportions from 23.6% ± 1.8% in the IMQ group and 23.3% ± 2.2% in the IMQ+Vehicle group to 13.9% ± 1.8% in the IMQ+BMS group ( F = 8.18, P = 0.003), whereas the VAS group showed a baseline proportion of 15.1% ± 6.4%, without altering neutrophil abundance. Multi-target analysis predicted mTOR and NQO1 as potential targets. Conclusion: Topical DSF ameliorates psoriasiform inflammation through multi-target effects on keratinocyte differentiation and immune cell function, accompanied by modulation of the IL-17A axis and CCL2/CCR2-related signaling. These findings support the potential repurposing of DSF as a nonsteroidal topical therapy for psoriasis.
Vitiligo is a common acquired depigmenting skin disorder characterized by melanocyte dysfunction or loss. It affects 0.5%–2.0% of the global population and imposes a substantial psychological burden. The pathogenesis involves genetic predisposition, oxidative stress, and immune dysregulation; distinct mechanisms underlie its progressive and stable phases. This review provides a systematic overview of recent advances in vitiligo treatment, from pathogenesis to clinical management, and emphasizes the importance of stage-specific therapy. During the active phase, management focuses on suppression of immune-mediated inflammation to halt disease progression. Key therapies include topical corticosteroids, calcineurin inhibitors, and Janus kinase inhibitors, all of which have demonstrated increasing efficacy. In the stable phase, the therapeutic objective shifts to repigmentation. Narrowband ultraviolet B phototherapy remains the cornerstone of treatment and is often combined with adjunctive therapies to enhance outcomes. Emerging research targeting tissue-resident memory T cells and the interleukin-15 pathway, along with strategies to restore the cutaneous microenvironment, offers promising approaches to prevent disease relapse. This review aims to inform clinicians of recent therapeutic advances and support optimal disease management, ultimately improving quality of life for individuals with vitiligo.
Extracellular trap formation (ETosis) is considered a novel form of cell death. These structures, composed of DNA, histones, and granular proteins, serve as a crucial defense mechanism against pathogen invasion. However, excessive extracellular trap formation can contribute to the development and exacerbation of inflammatory diseases, particularly psoriasis. Psoriasis is a chronic, multifactorial, immune-mediated inflammatory skin disorder that affects approximately 2%–3% of the global population. Although the mechanisms underlying psoriasis remain unclear, increasing evidence indicates that extracellular traps released by neutrophils, mast cells, macrophages, and lymphocytes are involved in its pathogenesis. This review provides a comprehensive overview of mechanisms underlying ETosis in the context of psoriasis, with a focus on the characteristics of extracellular traps, the immune cells involved, and their network interactions. It also explores novel pharmacological approaches that target extracellular traps, then discusses their translational prospects and clinical implications.
