Skin diseases are characterized by complex pathophysiology and substantial clinical heterogeneity. Their onset and progression involve multiple interconnected processes, including oxidative stress, chronic inflammation, disruption of the skin barrier, microbial dysbiosis, and impaired tissue repair, which often limit the ability of conventional therapies to achieve sustained disease control. Selenium nanoparticles (SeNPs) offer distinct advantages in dermatological treatment by combining the intrinsic biological activities of selenium, such as redox regulation and immunomodulation, with the engineering versatility of nanomaterials. However, therapeutic approaches that rely solely on the inherent bioactivity of SeNPs are increasingly insufficient to address the complexity of disease-associated microenvironments. Accordingly, the development of SeNPs into intelligent, multifunctional therapeutic platforms has emerged as an important direction in this field. Existing reviews have largely focused on the biological functions, preparation methods, or broad biomedical applications of SeNPs, whereas the engineering principles underlying their transition from intrinsically active nanomaterials to intelligent dermatological therapeutic platforms have not been systematically examined. This review therefore focuses on how the intrinsic functions of selenium can be translated, through materials and delivery engineering, into platform-level capabilities relevant to the treatment of skin diseases. By linking disease-specific pathological features and delivery barriers with corresponding design strategies, we propose a mechanism-guided framework for the rational development of SeNP-based dermatological nanomedicines.

Purpose:Objective longitudinal monitoring of a single psoriasis lesion remains underdeveloped. We evaluated the methodological feasibility of a quantitative fixed-target-lesion framework that derives continuous surface-color and vascular signals from dermoscopy, using CIELab as the measurement space rather than the clinical endpoint. Patients and Methods:This single-center retrospective longitudinal study included 28 patients with moderate-to-severe plaque psoriasis receiving biologic therapy (176 dermoscopic observations). Linear mixed-effects models (LMM) tested the longitudinal association between a* and PASI, and cumulative logit mixed models (CLMM) tested associations with ordinal dermoscopic scores. Data-driven a* thresholds were then applied unchanged to a separate mild-psoriasis cohort from the same center, device platform, and institutional database (BW cohort; 14 patients, 42 visit-level observations with concurrent scores) as a within-center transferability assessment. Results:a* was positively associated with PASI in the random-slope LMM (β = 0.928, p < 0.001). Data-driven a* tiers showed moderate agreement with expert background-color grading in the primary cohort (quadratic weighted κ = 0.538) and higher agreement in the unchanged-threshold BW assessment (κ = 0.722; ±1-level agreement 95.2%). The BW analysis was interpreted as within-center transferability, not external validation. Automated vessel-signal counts were associated with ordinal vessel-density scores (CLMM OR = 2.53 per SD, p < 0.001) and remained associated after adjustment for a* (OR = 2.13 per SD, p < 0.001). Exploratory treatment-group findings were treated as hypothesis-generating only. Conclusion:These findings provide proof-of-concept support for an objective, quantitative framework for monitoring fixed psoriatic target lesions. a* and rule-based vessel-signal counts are candidate lesion-level measures that may complement conventional scores, but clinical utility and cross-center or cross-device generalizability remain unestablished.

To propose and evaluate a CDASI-informed, medical-record-based site-by-lesion cutaneous phenotyping framework for anti-MDA5-positive dermatomyositis, using established systemic and immunological markers as reference anchors to examine whether this framework provides additional phenotypic resolution beyond conventional binary skin assessment. This single-centre retrospective cross-sectional study enrolled 339 anti-MDA5-positive DM patients. Cutaneous involvement was coded as binary ulceration, itch, and scale features across seven prespecified anatomical regions. The framework was CDASI-informed but did not use formal CDASI activity or damage scores. FLATCAN components, PAH, IgG, and IgM were used as systemic and immunological reference markers. Analyses included FDR-corrected univariate screening, hypothesis-driven multivariable association models, restricted cubic spline analysis, exploratory internal model-performance summaries, cross-correlation SVD (CC-SVD), and exploratory clustering. The framework revealed complementary skin-systemic association patterns. First, the spatial extent of ulceration refined a conventional binary ulcer signal: any cutaneous ulceration was associated with CD8 + T-cell depletion (OR = 3.35, P < 0.001; FDR q = 0.026), and ulcer site count remained independently associated with CD8 + depletion (OR = 1.43 per site, P = 0.008). Second, anatomical location contributed distinct information: facial ulceration was associated with PAH (OR = 2.28, P = 0.003) more strongly than overall ulcer site count. Third, lesion-feature type separated different immunological patterns, with ulceration preferentially associated with CD8+/IgG-related signals and itch with IgM-related signals. CC-SVD organised these observations into exploratory dimensions, including a bootstrap-stable facial involvement-PAH/infection dimension and a statistically less stable acral ulcer-CD8+/IgG dimension. Site-by-lesion cutaneous phenotyping may provide a useful framework for studying phenotypic heterogeneity in anti-MDA5-positive dermatomyositis. The observed associations are exploratory and require prospective validation using standardised skin assessment and clinical outcome follow-up. • A CDASI-informed site-by-lesion framework provides a structured way to organise cutaneous heterogeneity in anti-MDA5-positive DM. • Using established systemic and immunological reference markers as anchors, this framework revealed extent-, location-, and lesion-feature-dependent association patterns. • These findings support future prospective evaluation of structured cutaneous phenotyping, but do not establish a validated prediction tool or clinical decision rule.

BackgroundSSGJ-608 is an anti-interleukin-17A monoclonal antibody with high specificity and high affinity and has shown promising efficacy in treatment of moderate-to-severe psoriasis in preliminary trials.ObjectiveThis multicenter, randomized, open-label, phase 3 trial aimed to further evaluate SSGJ-608 at different dosing intervals (80mg every two weeks and 160mg every four weeks) in patients with moderate-to-severe plaque psoriasis.MethodsA total of 770 patients with moderate to severe plaque psoriasis were randomly assigned (1:1) to receive subcutaneous injections of 80mg of SSGJ-608 every two weeks (Q2W) after a starting dose of 160mg at week 0(608A group), or 160mg of SSGJ-608 every four weeks (Q4W) (608 B group) for 12 weeks. Efficacy was assessed by PASI75 and sPGA 0 or 1 response rates at week 12 as co-primary endpoints, and proportion of patients who achieved PASI90, PASI100 or sPGA score of 0 at week 12 as secondary endpoints. The safety profile was also evaluated.ResultsAt week12, the proportions of patients achieving PASI75 (92.7% vs. 95.1%) and sPGA 0/1 (80.3% vs. 79.0%) were comparable between the two SSGJ-608 dose regimens. The PASI90, PASI100 and sPGA 0 response rates were 81.0% vs.82.3%, 49.4% vs. 47.5%, and 49.4% vs.47.3% in the 608A group and the 608B group, respectively. In the subgroup of patients previously treated with anti-IL-17 therapy, SSGJ-608 also achieved high clinical response rates at week12. The most common TEAEs were hypertriglyceridemia, upper respiratory tract infection, hyperuricemia, increased alanine aminotransferase and hypercholesterolemia. Both treatment groups demonstrated a favorable safety profile and no new safety signals were identified.ConclusionsSSGJ-608 was highly effective for treating patients with moderate-to-severe plaque psoriasis at 80mg Q2W and 160mg Q4W in a larger population, especially in patients previously treated with anti-IL-17 therapy, and exhibited a favorable tolerability profile in Chinese patients with moderate-to-severe plaque psoriasis.Clinical trial registrationhttps://clinicaltrials.gov/, identifier NCT06299982.

Psoriasis is a chronic immune-mediated inflammatory disorder with systemic implications. While transcobalamin 2 (TCN2) has been linked to several autoimmune diseases, its role in psoriasis remains unclear. Here, we investigated the contribution of TCN2 to psoriatic pathogenesis. TCN2 expression was significantly elevated in both lesional skin and peripheral blood mononuclear cells (PBMCs) from psoriasis patients, and its levels declined following biologic therapy. Similarly, increased TCN2 expression was observed in imiquimod (IMQ)-induced psoriatic lesions in mice. To further evaluate its function, we generated Tcn2-deficient (Tcn2-/-) mice and established an IMQ-induced psoriasis model. Compared with wild-type controls, Tcn2-/- mice developed attenuated skin lesions with reduced epidermal hyperplasia and inflammation. Transcriptomic analysis of lesional skin revealed downregulation of inflammatory mediators (S100A7, S100A8, S100A9, IL-1β, IL-6) and suppression of STAT3 signaling in Tcn2-/- mice. In parallel, TCN2-knockdown HaCaT cells exhibited impaired proliferation due to G1-phase arrest, along with reduced expression of proinflammatory factors. Together, these findings demonstrate that TCN2 promotes keratinocyte hyperproliferation and amplifies inflammatory responses in psoriasis. In conclusion, this study identifies TCN2 as a previously unrecognized regulator of psoriatic inflammation and keratinocyte biology, highlighting its potential as a novel therapeutic target.

Background::Mendelian randomization (MR), polygenic risk score (PRS), Geno Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) are powerful bioinformatic analysis tools. However, the analysis of MR, PRS, GO, and KEGG may pose a challenge for novices. This article intends to introduce a program that adeptly guides beginners in implementing these analysis functions, ensuring that even those new to the field can confidently use them.Methods::The MPGK program was developed to run on the command line. It conveniently implements the MR, PRS, GO, and KEGG analysis functions by calling well-written R programs. The results of our analyses were validated using genome-wide association study (GWAS) summary data for diabetes and psoriasis, as well as gene sequencing data for diabetes.Results::Three demo analyses using the MPGK program demonstrate the comprehensive capabilities of the MPGK program in conducting advanced bioinformatics analysis. First, the MPGK program revealed a causal relationship between diabetes and psoriasis. Additionally, the PRS analysis generated polygenic risk scores for diabetes, demonstrating the implementation of PRS analysis within the MPGK framework. Furthermore, the GO and KEGG analyses indicated that psoriasis is associated with infection and T helper 17 cells. These findings are consistent with the previous literature.Conclusion::MPGK can be easily used to perform comprehensive analysis, including MR, PRS, GO, and KEGG analyses, by both beginners and researchers.

The long-term efficacy of biologics in psoriasis is compromised by primary or secondary resistance, and poor treatment adherence due to frequent dosing. We assessed the efficacy and safety of switching to an interleukin-23 subunit p19 (IL23p19) inhibitor picankibart at 200 mg every 12 weeks, without a washout period, on skin clearance and quality of life (QoL) in patients with plaque psoriasis. A total of 152 patients were enrolled, comprising 83 suboptimal responders (static Physician’s Global Assessment [sPGA] ≥ 2 or body surface area [BSA] ≥ 3

Pachyonychia congenita tarda (PCT) is a rare late-onset variant of pachyonychia congenita (PC), with its nosological status remaining controversial due to limited molecular confirmation in adult-onset cases. We report a 57-year-old Chinese woman who presented with a four-year history of progressive, painful thickening of all 20 nails, accompanied by mild palmoplantar keratoderma. Repeated mycological examinations were negative, and no clinical improvement was observed after prolonged antifungal therapy. Familial segregation analysis could not be performed because biological samples from relatives were unavailable, and the patient reported no known affected relatives. Whole-exome sequencing (WES), followed by Sanger confirmation, identified a heterozygous missense variant in KRT6A (c.661C>A, p.Leu221Ile), predicted to be pathogenic. Notably, the mutation is located outside the highly conserved helix boundary motifs (HBM), in contrast to classic PC-associated variants that typically present in early childhood. The patient's phenotype was relatively mild and characterized by isolated late-onset nail dystrophy. To our knowledge, this case represents the latest reported onset of PCT, occurring at 53 years of age, and provides molecular evidence supporting PCT as a distinct clinical entity rather than a misdiagnosis of other keratinization disorders. We further propose that mutations outside HBM regions, combined with conservative amino acid substitutions, may preserve partial keratin function and delay disease manifestation until later in life. In conclusion, PCT should be considered in the differential diagnosis of treatment-resistant onychomycosis, particularly in older adults, and WES may serve as a valuable tool for accurate diagnosis.

Background:Skin is the largest organ of the human body. It continuously encounters environmental toxicants, including airborne pollutants, which may induce many skin disorders, such as psoriasis. However, evidence on the association between airborne pollutants and psoriasis prevalence in China remains limited. Methods:We used nationwide inpatient diagnostic data on psoriasis from 2021 to 2023, encompassing 149 744 cases across 31 provinces, municipalities, and autonomous regions in China, along with corresponding air pollution data. We analysed the spatial distribution and clustering patterns of psoriasis using the spatial autocorrelation analysis. We employed Pearson correlation analysis and Geodetector to explore the spatial heterogeneity of psoriasis and its association with airborne pollutants at the provincial level. We assessed the explanatory power of individual airborne pollutants and their combined effects on psoriasis prevalence. Results:Pearson correlation analysis revealed that PM10 (r = 0.604), PM2.5 (r = 0.429), air quality index (AQI) (r = 0.542), and NO2 (r = 0.476) have significant positive correlations with psoriasis prevalence. Psoriasis and its subtypes exhibited significant spatial heterogeneity and diverse clustering patterns across regions. Geodetector identified PM10 (q = 0.357; P = 0.000), AQI (q = 0.315; P = 0.000), and O3 (q = 0.264; P = 0.000) as key contributors to this spatial heterogeneity. Interactive detection analysis further revealed that the combined effects of specific pollutant pairs, including PM2.5 and SO2 (q = 0.790), PM10 and SO2 (q = 0.727), as well as O3 and SO2 (q = 0.704), played a pivotal role in explaining the prevalence of psoriasis. The other combinations also showed an important impact on psoriasis subtypes, including psoriasis vulgaris (PM2.5 and SO2) (q = 0.792), psoriasis erythematous (PM2.5 and SO2) (q = 0.852), psoriatic arthritis (PM10 and O3) (q = 0.840), and nail psoriasis (PM10 and O3) (q = 0.789). Conclusions:The airborne pollutants influence psoriasis prevalence and its subtypes. With the largest global study of the Asian population, we provide novel insights into the impact of air pollution on psoriasis, guiding future public health policies and clinical interventions.

Background:Accurate quantification of skin color is essential for dermatologic research and clinical practice. Conventional methods rely on specialized equipment, trained operators, and high costs. Smartphone-based technologies provide a promising alternative for accessible skin color assessment. Objective:To evaluate the reliability and validity of the smartphone-based skin colorimeter application, You Look Good Today (YLGTD), for facial skin color assessment compared with two validated devices, VISIA and DermaLab Combo. Methods:A total of 105 Chinese participants with healthy facial skin were enrolled. Cheek skin color measurements were obtained using YLGTD (user self-assessment and physician measurement modes), VISIA, and DermaLab Combo. Inter-rater reliability between YLGTD measurement modes was assessed using intraclass correlation coefficients (ICC) and Bland-Altman analysis. Criterion validity was evaluated using Pearson's correlation coefficients between YLGTD measurements and the reference devices. Results:YLGTD demonstrated excellent inter-rater reliability across all parameters (ICC: 0.85-0.95). Bland-Altman analysis showed small biases between the two measurement modes for the L, a, and b (-0.05, 0.18, and -0.99, respectively). For criterion validity, YLGTD in user mode showed strong correlations with DermaLab Combo for L* (r = 0.71), individual typology angle (ITA°, r = -0.81), and chroma (C*, r = 0.78), and moderate correlations for b* (r = 0.59) and hue (h°, r = 0.57). Correlations were consistently stronger in physician mode (L*: r = 0.77; b*: r = 0.75; C*: r = 0.84; ITA°: r = -0.87). VISIA showed a stronger correlation for a* (r = 0.55) but weaker correlations for L* (r = 0.56) and ITA° (r = -0.68) compared with YLGTD. Conclusion:The smartphone-based application YLGTD demonstrated excellent reliability and acceptable validity for facial skin color assessment, particularly for pigmentation-related parameters. Its standardized measurement workflow and integrated algorithms enable consistent skin color evaluation across devices and real-world conditions, providing a convenient and cost-effective approach for objective skin color assessment.

Atopic dermatitis (AD) is a complex chronic inflammatory skin disease driven by skin barrier dysfunction, immune dysregulation, and microbial imbalance. Traditional sampling methods, such as biopsies and blood collection, have provided valuable pathophysiological insights. However, their invasiveness, associated discomfort, and limitations for repeated sampling have constrained a dynamic understanding of disease progression and treatment responses. In recent years, skin tape stripping (STS) has emerged as a minimally invasive or even non-invasive technique that addresses these limitations. STS enables the collection of corneocytes and upper granular layer cells from the epidermis, and when combined with high-throughput multi-omics technologies, such as RNA sequencing, proteomics, lipidomics, and metatranscriptomics, it provides a powerful platform to dissect the molecular mechanisms of AD, identify novel biomarkers, and facilitate stratification in precision medicine approaches.

We conducted the largest-ever cross-ancestry GWAS meta-analysis for SLE with 25,109 cases and 271,084 controls comprising East Asian (EA), Southeast Asians (SEA) and Europeans (EUR). We identified 279 independent non-MHC associations, including 51 unreported SLE associations, among which EA-driven associations were identified at PIK3AP1, FOXK1, UBASH3A, and CTDSP1. We further identified a significant interactive association between FOXK1 and IRF5 variants. Statistical fine-mapping together with SNP-to-gene inference and functional prediction identified plausible causal non-coding variants in PRKD3 and TSPAN32, as well as variants in enhancers for CD83, IL12A, c-MYC, and l-MYC, along with an EA-specific missense variant rs55882956 in TYK2. Transcription factors (TFs) linked to fine-mapped enhancer variants contributed to trans-acting regulatory mechanisms in SLE, with strong heritability enrichment at their binding sites across various immune cell types. These include a disproportionate representation of B cell TFs that are themselves risk genes. MYC protein showed the largest enrichment at its binding sites in B cells. In addition, Prioritizing MYC binding sites of B cells in polygenic risk score improved SLE prediction. We also identified 67 candidate druggable genes, providing mechanistic insights and highlighting opportunities for therapeutic development in SLE.

Dysbiosis of the skin microbiome, characterised by Staphylococcus aureus overgrowth and imbalance of commensals such as Staphylococcus epidermidis (S. epidermidis), is closely associated with atopic dermatitis (AD). However, the therapeutic relevance of defined S. epidermidis-associated indole metabolite, especially indole-3-acetic acid (IAA), in AD-like inflammation remains incompletely characterised. Here, we investigated the role of IAA, a tryptophan-derived metabolite enriched in the culture supernatant of the tested S. epidermidis strain, in AD-like inflammation. Public transcriptomic analyses suggested impaired AHR-associated and tryptophan-metabolism signatures in AD skin, particularly in lesional skin, while human metagenomic data indicated AD-associated staphylococcal alterations. Targeted metabolomics identified IAA as an enriched indole metabolite in S. epidermidis culture supernatant. In an MC903-induced AD-like mouse model, cutaneous IAA levels and S. epidermidis abundance were reduced. Topical IAA attenuated AD-like phenotypes, improved barrier-related proteins and reduced inflammatory indices. These protective effects were diminished by the AHR antagonist CH223191. Molecular docking predicted a possible interaction between IAA and AHR, and in vitro assays showed that IAA modulated keratinocyte AHR-associated inflammatory and barrier-related responses. Together, our findings support IAA as a microbiome-associated postbiotic candidate for AD management, at least partly through AHR-associated signalling.

Background Chimeric antigen receptor (CAR) -T cell therapy has emerged as a promising approach for treating severe autoimmune diseases (AIDs), offering distinct advantages over conventional immunosuppressive therapies. This review examines recent advancements in both autologous and allogeneic CAR-T platforms for AIDs.Methods We analyzed preclinical and clinical evidence regarding CAR-T therapies. These therapies target signaling molecules across various cells in the myeloid and lymphoid lineages, addressing autoimmune pathologies across dermatological, neurological, gastrointestinal, and hematological systems.Results Diversified CAR-T technological innovations have been developed. CAR-T therapy achieves remarkable efficacy in various AID by precisely eliminating pathogenic cells and facilitating a systemic immune reset, thereby maintaining a favorable balance between therapeutic benefit and safety.Conclusion CAR-T cell therapy represents a revolutionary therapeutic strategy for the management of refractory AIDs. Addressing current challenges will further promote its clinical translation and expand its application in the treatment of AIDs.

In a cohort of 3612 atopic dermatitis patient-partner dyads, we evaluated agreement between clinician-rated severity (SCORAD) and independent patient- and partner-reported symptom severity (POEM/partner-POEM), and explored links with short-term response (EASI 90 at week 20) and work functioning. Patients and partners reported symptom severity very similarly, yet discordance with SCORAD was concentrated in moderate disease; higher baseline agreement was associated with better short-term response. Partner burden - including sleep loss and depressive symptoms - rose with clinician-rated severity and correlated with work limitation in employed dyads.

BACKGROUND AND OBJECTIVES:Psoriasis is a chronic inflammatory skin disease, and noninvasive diagnostic tools are essential for accurate diagnosis and treatment monitoring. Multiphoton microscopy (MPM) enables real-time, noninvasive skin imaging with submicron resolution. This study evaluated the diagnostic accuracy of MPM in psoriasis and its potential application in therapeutic monitoring. PATIENTS AND METHODS:This prospective observational study enrolled 34 patients with psoriasis. It comprised three parts: (1) analysis of imaging features of lesional and nonlesional skin using multiphoton microscopy (MPM; Transcend Vivoscope); (2) evaluation of the diagnostic performance of MPM parameters compared with reflectance confocal microscopy (RCM); and (3) prospective monitoring of 24 patients treated with Benvitimod (Tapinarof) cream for 8 weeks (T0/T1/T2). RESULTS:MPM detected psoriasis characteristics (including hyperkeratosis, parakeratosis, an absent stratum granulosum, enlarged nucleus diameter, and absent bright rimming) with comparable diagnostic efficiency to RCM (AUC = 0.838, p < 0.001 vs. 0.824, p < 0.001). Psoriatic lesions showed significant perinuclear fluorescence accumulation compared to healthy skin (p < 0.001). All imaging features improved significantly after 8 weeks of treatment (p < 0.001). PASI/TLS scores showed correlations with the epidermal thickness (r = 0.403/0.492, p < 0.001), nuclear diameter (r = 0.4/0.375, p < 0.001), and fluorescence intensity (r = -0.419/-0.492, p < 0.001). CONCLUSIONS:MPM is a novel and non-invasive imaging technique for psoriasis evaluation and treatment monitoring.

Herpes zoster (HZ), caused by varicella-zoster virus reactivation, is characterized by painful dermatomal eruptions. Systemic metabolic alterations during acute infection remain incompletely defined. In this exploratory case-control study, serum samples from 47 acute HZ patients and 30 healthy controls were analyzed using untargeted ultra-high-performance liquid chromatography-high-resolution mass spectrometry. Differential metabolic features were identified using models adjusted for age and analytical batch (p < 0.05; FC ≥ 1.2 or ≤ 0.83). Pathway enrichment was explored by over-representation analysis. A nested cross-validated LASSO-logistic regression model incorporating selected metabolites, age, and batch was constructed to assess exploratory internal discrimination. Thirty-eight differential metabolic features were identified, involving nucleoside, amino acid, lipid, and energy metabolism. Pyrimidine-related and amino acid-related pathways appeared among the leading nominal pathways. A four-metabolite panel (Uridine/Pseudouridine, Uracil, 2-Pyrrolidinone, and L-Methionine), combined with age and batch, yielded an internal cross-validated AUC of 0.91 (95% CI: 0.8369-0.9688). These four core metabolic features retained the same directions of change in the age-overlap sensitivity cohort, with nucleoside-related features elevated and L-Methionine decreased in HZ patients. Acute HZ is associated with alterations in serum metabolic features, particularly involving nucleoside-related and amino acid-related signals. These exploratory findings provide a metabolic overview of acute HZ and require validation in independent, age-matched cohorts.

AIMS:This study aimed to elucidate the role of oligoadenylate synthase-like protein (OASL) as a pivotal regulator integrating keratinocyte hyperproliferation, inflammation, and lipid metabolic dysregulation in psoriasis pathogenesis. MATERIALS AND METHODS:Clinical analyses compared epidermal OASL expression levels between psoriasis patients and healthy individuals. Functional studies in HaCaT cells employed OASL knockdown and overexpression to assess effects on proliferation, inflammatory responses, and lipid metabolism. The JAK1-STAT1-OASL regulatory axis was investigated using the JAK1 inhibitor Upadacitinib. The natural flavonoid Astilbin was screened as an OASL inhibitor, and its therapeutic efficacy was evaluated in imiquimod-induced psoriatic mice. KEY FINDINGS:OASL was significantly upregulated in psoriatic epidermis. Knockdown of OASL suppressed keratinocyte proliferation and inflammation, while its overexpression promoted hyperproliferation, inflammation, and lipid metabolic dysregulation via p38 MAPK pathway activation. Mechanistically, Upadacitinib reduced OASL expression by inhibiting STAT1, confirming the JAK1-STAT1-OASL axis. Astilbin markedly alleviated imiquimod-induced psoriasiform dermatitis in mice. SIGNIFICANCE:This study reveals OASL's pivotal regulatory role in psoriasis and its associated pathways, providing novel therapeutic targets and a potential natural drug candidate. These findings establish a theoretical foundation for developing multi-targeted strategies against psoriasis.

To the Editor: The rapid evolution and widespread adoption of cloud computing, big data, and artificial intelligence have significantly accelerated the digital transformation of medical institutions. However, this progress has led to a rise in the incidence and costs of data breaches, with the average breach costing approximately $15 million in the USA.[1] Such breaches pose serious threats to national security and public welfare, underscoring the urgent need for robust data protection and compliance in healthcare. Despite the benefits of advanced information technology, hospitals face substantial challenges in ensuring data security and compliance. To address these challenges, we proposed a four-step solution for developing secure and compliant intelligent hospitals, providing a reference framework for data protection and compliance in the healthcare industry [Figure 1A].Figure 1: Summary of the work. (A) The four-step solution for DCM. The key elements in each step are listed. (B) Block-chain-based real-time data compliance monitoring system. This monitoring system simulates the data management life cycle within medical settings, ensuring timely review of data compliance practices, providing risk alerts accordingly, and offering robust assurance when data flows across different entities. The life cycle of data from data provider to data visitor is illustrated with associated data handling, and detailed explanations are provided in the Supplementary File, https://links.lww.com/CM9/C266. (C) An illustration of classic privacy computing-based medical research platform. The figure demonstrates the data supervision and integration process within a healthcare data management system, illustrating the flow and control of data from request submission to final data cleaning and integration. The process is divided into four main sections as follows: Data applicator, Central control, Data provider, and Quality control. Detailed explanations are provided in the Supplementary File, https://links.lww.com/CM9/C266. DCM: Data compliance management.The first step is to conduct comprehensive data compliance risk assessment and develop the corresponding legal framework. Medical institutions need to identify and compile all relevant laws, regulations, and national standards [Supplementary Table 1, https://links.lww.com/CM9/C266]. Following this, they must assess existing compliance systems to identify vulnerabilities using the gathered information. Based on these insights, institutions should design and implement a data compliance management (DCM) system that includes data security measures, emergency planning, and risk assessment protocols. The second step involves establishing an organizational structure and cultivating professional staffing, which are crucial for any service-oriented organization. To enhance the implementation of management plans and allocate sufficient manpower and resources, we advocate for the creation of a department of DCM with a three-tier management system: (1) Central coordination: The director of DCM is responsible for overarching policy decisions, ensuring alignment with legal requirements, and resource allocation. (2) Departmental coordination: This includes directors of each department, who are tasked with implementing policies, conducting risk assessments, and monitoring compliance at the departmental level. (3) Operational teams: These teams handle day-to-day data processing, ensuring adherence to protocols set by higher tiers. Their responsibilities include formulating and implementing institution-wide information security strategies; supervising and inspecting compliance with security management practices; regularly evaluating the security and availability of patient information; updating the business information system periodically; and conducting ongoing staff training, continuous education, and periodic certification. The third step is to strengthen the management supervision and foster a culture of data compliance. Given that the data security encompasses the entire life cycle of data, stringent security supervision is critical. We advocate for the establishment of a specialized supervisory body to oversee the daily management and effective use of data. This body should fulfill the following functions: (1) exercise autonomous authority to monitor and address medical information security issues; (2) develop structured supervisory system, standardize inspection methodologies, and establish key performance indicators to enhance system operability; (3) define clear governance objectives and assessment criteria and regularly evaluate the implementation of safety rules and regulations; and (4) develop rapid response strategies to swiftly address instances of non-compliance or breaches. Engaging independent third-party auditors adds an additional layer of scrutiny and transparency, helping to identify potential gaps overlooked by internal teams. Regular external assessments ensure that security measures and practices remain robust and aligned with evolving standards and regulations. Furthermore, embedding the importance of data compliance into the organizational culture is fundamental. Medical institutions are encouraged to strengthen personnel ethics through comprehensive training and certifications, regularly updating these programs to reflect current best practices and regulations. Routine assessments to gauge awareness of legal issues and ensure the compliant use of information systems should be conducted regularly. The fourth step involves incorporating advanced techniques to achieve intellectualization and standardization of DCM. Embracing advanced technologies not only furthers the digitalization of the healthcare system but also helps resolve potential conflicts between technical implementation and legal compliance. Based on the past practice and legal considerations, we recommend integrating the following technical areas: 1. The office system should include DCM functions, encompassing the following three main modules [Supplementary Figure 1, https://links.lww.com/CM9/C266]: (1) a clearly delineated staffing structure; (2) integrated rules and regulations; (3) portal for external agencies and experts that facilitate interactions. 2. Patient authorization management platform [Supplementary Figure 2, https://links.lww.com/CM9/C266]. The platform should: (1) facilitate unified patient authorization across multiple medical information systems via a central authorization portal; (2) automatically update regulatory requirements and generate tailored patient consent forms to comply with current mandates; (3) issue risk warnings and timely alerts to prevent unauthorized data use or breaches; and (4) implement an enterprise master patient index to integrate patient information using a unique patient ID, ensuring the accuracy and integrity of personal information across various platforms. 3. Block-chain-based real-time data compliance monitoring system [Figure 1B and Supplementary Figure 3, https://links.lww.com/CM9/C266]. Block-chain technology ensures the accuracy, completeness, and timeliness of clinical trial data while facilitating the recording and deposition of compliance statuses.[2,3] This monitoring system leverages block-chain to provide comprehensive oversight of data compliance, thereby enhancing the reliability and security of medical data management. 4. Privacy computing-based medical research platform [Figure 1C and Supplementary Figure 4, https://links.lww.com/CM9/C266]. Privacy computing integrates cryptography, artificial intelligence, and secure hardware, focusing on the following three main areas: multi-party computation, federated learning, and trusted execution environments.[4] This approach encrypts data and operates within a secure computing environment, ensuring the safety of medical data sharing, even in multi-center studies. 5. Medical data analysis and processing system. This system scans various datasets, classifies, analyzes, and utilizes data according to its security level. For user-authorized information, it works with the authorization platform to ensure proper handling. To achieve these objectives, the system should be equipped with: (1) compliance processing templates for different data types; (2) the ability to intelligently scan, evaluate, classify, and desensitize data automatically; and (3) automatic selection of processing approaches based on the specific purposes of data handling. "Internet healthcare" offers significant benefits to individuals and healthcare organizations by reducing costs, enhancing speed and flexibility, and facilitating communication.[5] However, these advancements also introduce substantial security risks. To address these multifaceted data security challenges, we propose a four-step solution that encompasses legal and technical aspects while emphasizing the importance of management supervision and culture cultivation. This framework aims to provide a concise yet comprehensive approach to practice data compliance in medical settings. Funding This study was supported by grants from the National Key R&D Program of China (Nos. 2024YFF0507404 and 2022YFC3602002), National High Level Hospital Clinical Research Funding (No. 2022-NHLHCRF-LX-02-03) and The Supply of High-quality Data Sets (No. 2024-13).