JID Innovations

Early detection of suspicious moles remains the most effective means of reducing mortality from skin cancer, yet systematic screening is constrained by the time and expertise required for manual mole assessment. This paper presents an end-to-end computational pipeline that utilizes wide-angle skin photographs (including consumer-grade smartphone images) and produces quantitative ABCD (Asymmetry, Border irregularity, Color variegation, Diameter) feature scores for every detected mole. The pipeline operates in four stages: mole detection via adaptive thresholding and blob analysis, super-resolution enhancement using EDSR, false-positive filtering using a brightness-based statistical criterion, and lesion segmentation using the Boundary Attention Mapper (BAM). BAM generates high-resolution segmentation masks by fusing early-layer activations with GradCAM heatmaps from a trained EfficientNet-B7 classifier, achieving 90.45% accuracy on the ISIC2017 dataset, outperforming both conventional GradCAM (87.78%) and dedicated segmentation architectures, including DeepLabv3 and SAM v2 by more than 5 percentage points in Dice score. The EfficientNet-B7 backbone achieves a micro-average AUC of 0.97 across eight lesion classes, with a melanoma AUC of 0.99. Color quantification uses K-means clustering with a threshold calibrated on the PH2 dataset (MSE = 1.425). Applied to 87 wide-angle images, the mole detection module achieved an F1 score of 86%. The system outputs a structured CSV of per-lesion ABCD scores suitable for clinical triage and longitudinal tracking. A clinical validation study with dermatologists and surgeons is underway to assess concordance between automated and expert assessments.

Oculocutaneous albinism type 1 (OCA1) is a pigmentation disorder caused by biallelic tyrosinase (TYR) mutations, an essential enzyme for melanin synthesis. TYR inactivity results in loss of hair, skin, and eye pigment, which is detrimental for ocular function. Hypopigmentation of iris, retinal pigment epithelium (RPE), and choroid results in severe photosensitivity and low visual acuity. There are currently no FDA-approved pigment restoring therapies for OCA1, making therapeutic development an unmet clinical need. To address this gap, we have advanced an adeno-associated viral (AAV)-mediated Tyr replacement approach for OCA1 ocular pigment restoration. We evaluated the optimal viral delivery strategy and vector cell-type specificity for iris, RPE, and choroid pigmentation in an OCA1 mouse model, testing intraocular and systemic viral delivery methods in conjunction with viral constructs of varying RPE-specificity. Early, systemic delivery of an RPE-directed AAV-Tyr construct, AAV9.2yf-VMD2-Tyr, achieved widespread ocular pigment rescue with minimal off-target expression in non-ocular tissues. Animals treated with AAV9.2yf-VMD2-Tyr demonstrated reduced photophobic behavior compared to untreated controls, indicating that ocular pigmentation restores a debilitating functional consequence of OCA1. Our findings establish a foundation for clinical translation of an AAV-TYR therapy aimed at improving light sensitivity, glare, and low vision through pigment restoration in patients with OCA1.

The aim of this study was to explore the scalp bacterial flora structure and functional characteristics in androgenetic alopecia (AGA) patients, analyze its association with disease phenotypes and unhealthy lifestyles, and provide a basis for clarifying AGAs microecological pathogenic mechanism and targeted interventions. A total of 7 AGA patients and 6 healthy controls (HC) were enrolled, with scalp microbial samples collected. High-throughput sequencing of the 16S rRNA V3-V4 region was used to analyze flora alpha/beta diversity, species composition and differential species. LEfSe and KEGG functional prediction screened marker bacteria and differential pathways, and clinical/lifestyle data were collected for inter-group comparisons. No significant difference in Chao index was observed between groups (P>0.05), but Shannon/Simpson indices/Pielou evenness (P<0.01) and intra-group Bray-Curtis distance (P<0.001) were significantly higher in the AGA group, indicating reduced community stability. Staphylococcus dominated healthy scalps; the AGA group had fewer symbiotic bacteria but enriched Acinetobacter, Pseudomonas, andCutibacterium. LEfSe identified Firmicutes/Staphylococcus as HC markers and Proteobacteria/Gammaproteobacteria/Acinetobacter/Pseudomonas as AGA dysbiotic flora. KEGG showed upregulated metabolic, immune and cell motility pathways in AGA (P<0.05), with only infectious diseases pathway enriched in HC. AGA patients had more frequent hair washing and higher rates of staying up late, high-fat diet and insufficient fruits/vegetables (all P<0.05). In conclusion, AGA patients have typical scalp microecological dysbiosis closely related to unhealthy lifestyles, which may accelerate alopecia by inducing follicular inflammation. Scalp flora can be potential biomarkers and targets for AGA assessment and intervention.

Background Lichen Planus (LP) is a chronic inflammatory disorder that can affect the skin, hair, nails, and mucous membranes. Oral lichen planus (OLP), the most common LP subtype, is a disease of the oral mucosa, often diagnosed through clinical examination and histopathological confirmation. Extracellular vesicles (EVs) transfer proteins, lipids, and nucleic acids among cells and have become increasingly studied for their potential as minimally invasive diagnostic biomarkers and therapeutic agents in inflammatory and autoimmune diseases. Methods PUBMED and Embase were searched from inception through June 27th, 2026. Human studies investigating EV-associated miRNA or protein biomarkers in LP and its subtypes were included, with risk of bias assessed using a modified Newcastle-Ottawa Scale. Diagnostic accuracy was evaluated using receiver operating characteristic (ROC) and BRMA models when sufficient data were available. Results Ten articles met the inclusion criteria, encompassing biomarker discovery, functional, and mechanistic studies of EVs in OLP. These included studies (n = 10) comprised 298 individuals with LP (weighted mean age 50.7 years; 61.5% female) and 194 controls (weighted mean age 47.8 years; 58.5% female). OLP-specific cohorts (n = 9 studies) included 261 individuals with OLP (weighted mean age 50.7 years; 61.4% female). Although no individual EV-associated miRNAs or proteins overlapped across studies, EV-associated miRNAs demonstrated substantial heterogeneity, while EV-associated protein findings centered on pathways related to antigen presentation, inflammatory signaling, and immune activation. Several candidate biomarkers, including miR-4484, miR-34a-5p, GJA1, PDIA3, and Cx43, showed potential diagnostic or prognostic relevance. ROC analyses demonstrated good diagnostic utility for miR-4484 (AUC = 0.81), and the combination of GJA1 and Cx43 showed the strongest discriminatory ability (AUC = 0.892). The diagnostic accuracy meta-analysis showed good discrimination (pooled AUC = 0.89). Functional and mechanistic studies suggested that EVs may actively contribute to OLP pathogenesis through promoting epithelial injury and activating inflammatory signalling pathways. Conclusions EV-associated miRNAs and proteins are potential biomarker candidates for LP and may provide insight into the inflammatory and immune mechanisms underlying disease pathophysiology. Functional and mechanistic evidence further suggests that EVs may play an active role in disease progression. However, current evidence has limitations such as small sample sizes and methodological heterogeneity. Larger, standardized, and longitudinal studies are needed to v

Fibroproliferative diseases such as systemic sclerosis are complex conditions characterized by chronic skin inflammation and progressive fibrosis, with fibroblast activation as a central feature. While Transforming Growth Factor Beta (TGF-{beta}) signaling is a well-established driver of fibrosis in SSc, inflammatory pathways such as Nuclear Factor Kappa B (NF-{kappa}B) also contribute substantially to disease morbidity. We previously identified CD109 as a TGF-{beta} co-receptor and negative regulator of fibrotic signaling; however, its role in inflammatory signaling remains unknown. Here, we investigate the function of CD109 in regulating inflammatory signaling in skin fibroblasts. We show that, CD109 co-localizes and associates with Toll-like receptors (TLR2, TLR4) and tumor necrosis factor receptors (TNFRI, TNFRII), and that loss of CD109 enhances TNF--induced NF-{kappa}B activation and reprograms cytokine production in human dermal fibroblasts. Furthermore, both global and fibroblast-specific CD109 knockout mice exhibit increased immune cell infiltration and skin inflammation. In parallel, single-cell transcriptomic analyses across a pan-disease fibroblast atlas show that CD109 expression is preferentially maintained in structural and homeostatic fibroblast subtypes, whereas immune-interacting fibroblast subsets consistently display decreased CD109 levels. Pathway-level analyses of fibroblast pseudobulk samples reveal altered activity of canonical inflammatory pathways in SSc compared to healthy skin. Together, these findings identify CD109 as a fibroblast-intrinsic negative regulator of inflammatory signaling and suggest a broader role for CD109 in modulating inflammatory responses in systemic sclerosis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/736423v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@be9e08org.highwire.dtl.DTLVardef@794173org.highwire.dtl.DTLVardef@b81eb5org.highwire.dtl.DTLVardef@1e811f5_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract: CD109 Restrains Fibroblast-Driven Inflammation by Modulating NF-{kappa}B Signaling. Generated using FigureLabs.ai and edited using Adobe Photoshop. C_FIG

Background Growing evidence suggests that the gut microbiome influences nasal and ocular allergic inflammation through gut-mucosal immune interactions. Yet, its association with Allergic rhinitis (AR) and allergic eye symptoms (AES) remains incompletely understood in large population-based cohorts. Objective To examine associations between the gut microbiome and self-reported AR and AES in Finnish adults. Methods Shallow metagenomic sequencing was performed on stool samples from a population-based cohort (FINRISK02; n = 7,231). Microbial taxonomic and functional profiles were compared between individuals with AR (n = 1,950), AES (n = 1,554), combined allergies (AR and/or AES; n = 2,305), and controls without reported symptoms (n = 3,175). Results Allergic groups exhibited lower microbial richness and phylogenetic diversity than controls. Shared microbial and functional signatures were observed across AR and AES, consistent with their high co-occurrence (N = 1,199). Compared with controls, allergic groups showed enrichment of 17 bacterial species, predominantly from the Clostridia class, including taxa previously associated with asthma, chronic obstructive pulmonary disease, and atopic dermatitis. Allergic individuals also exhibited enrichment of pathways related to mucosal carbohydrate processing, shikimate metabolism, histidine turnover, and broader amino acid metabolism. Concurrent enrichment of histidine biosynthesis and degradation suggested altered microbial histidine metabolism. Conclusions Adult allergic symptoms are associated with gut microbiome taxonomic and functional alterations linked to mucosal barrier function and immune-related metabolism, supporting a shared gut-mucosal immune axis across allergic phenotypes.

Dermatomyositis is driven by overactivation of type I and II interferons and other proinflammatory cytokines that signal via the JAK-STAT pathway. We conducted a 12-week, open-label study of brepocitinib, an oral TYK2/JAK1 inhibitor, in five adults with severe cutaneous dermatomyositis. Treatment was associated with rapid, clinically meaningful improvement in cutaneous disease activity. Single-cell and spatial transcriptomic profiling of lesional skin showed marked suppression of interferon-responsive pathways and inflammatory cell states by week 4. Together with findings from a Phase 3 randomized trial in DM patients with skin and muscle involvement (VALOR, NCT05437263), these data support TYK2/JAK1 inhibition as a promising therapeutic strategy for DM.

Background: HIV infection has long been associated with increased incidence of severe cutaneous adverse reactions (SCAR). It remains unknown whether this increased incidence is a direct biological result of HIV infection, differences in drug exposure, or other demographic factors. Objective: To evaluate the association between HIV and SCAR and determine whether this relationship persists after adjusting for demographic factors and structured drug exposure. Methods: We analyzed reports from the FDA Adverse Event Reporting System (FAERS) from 2013-2023. SCAR outcomes included Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN), drug reaction with eosinophilia and systemic symptoms (DRESS), acute generalized exanthematous pustulosis (AGEP), and generalized bullous fixed drug eruption (GBFDE). HIV status was determined using antiretroviral exposure, indication text, and machine-learning imputation. Logistic regression models were constructed sequentially: unadjusted, demographic-adjusted, and fully adjusted with drug principal components to account for polypharmacy. Drug-level disproportionality and HIV-drug interaction analyses were also performed. Results: In unadjusted models, HIV was strongly associated with SCAR (OR ~2.0-2.7). Adjustment for demographics attenuated this association, and further adjustment for drug exposure reduced the effect to near null for overall SCAR and DRESS. A modest residual association persisted for SJS/TEN (OR ~1.3). Disproportionality analyses demonstrated enrichment of specific high-risk drugs in PLWH. Interaction modeling revealed drug-specific amplification of SCAR risk in HIV, notably for carbamazepine and clarithromycin, whereas other drugs showed minimal interaction. Conclusion: The association between HIV and SCAR is largely explained by differences in drug exposure and demographic factors. Residual risk is drug-specific rather than uniform, supporting a model in which HIV modifies susceptibility to select drug triggers rather than acting as a global risk factor. Further prospective and retrospective studies are required to quantify associations.

Background Erythema nodosum leprosum (ENL) is a severe immune-mediated complication of multibacillary leprosy requiring prolonged immunosuppression. Steroid-sparing agents are essential to reduce relapse and treatment-related morbidity. Methods This longitudinal analytical observational study compared outcomes in patients with ENL treated with prednisolone plus thalidomide (Group A; n=30) and prednisolone plus tofacitinib (Group B; n=31). Patients were followed for 6 months. Primary outcomes included relapse rate and ENLIST ENL Severity Score (EESS). Secondary outcomes were neutrophil-lymphocyte ratio (NLR), Dermatology Life Quality Index (DLQI), steroid dependency, and adverse events. Inter-group comparisons and longitudinal analyses were performed using non-parametric tests. Correlations between NLR, EESS, and DLQI were assessed using Spearmans rank correlation. Results Relapse occurred in 36.7% of patients in Group A and 71.0% in Group B (p=0.007). The mean number of relapses was significantly lower in Group A (0.70{+/-}1.06 vs 1.84{+/-}1.51, p=0.002). At 3 and 6 months, Group A demonstrated significantly lower NLR values (p=0.017 and p<0.001, respectively). DLQI and EESS scores improved in both groups; however, sustained improvement was more consistent in Group A. Steroid-free status at 6 months was achieved in 93.3% of Group A compared with 58.1% of Group B (p<0.001). NLR showed a positive correlation with EESS ({rho}=0.269, p=0.018) and DLQI ({rho}=0.604, p<0.001) at 6 months. On multivariable logistic regression analysis adjusting for baseline confounders, patients receiving tofacitinib had significantly higher odds of relapse compared with those receiving thalidomide (adjusted OR 9.87, 95% CI 1.73-27.12; p = 0.006).Adverse events were predominantly mild to moderate, with differing safety profiles between groups. Conclusion Thalidomide demonstrated superior relapse prevention and steroid-sparing efficacy compared with tofacitinib in ENL. NLR correlated with disease severity and quality of life, supporting its role as a useful biomarker for monitoring disease activity during follow-up.

Objective: To evaluate the effect of residual hair (RH) biomaterial particulates, biphasic electrical stimulation (ES), and their combination (RHES) on the kinetics and quality of skin wound healing. Method: Eighteen adult albino mice received bilateral, splinted 10-mm full-thickness dorsal excisional wounds and were randomly assigned to one of three animal groups producing four wound-level treatment conditions: untreated control (-) (n = 12), RH (n = 12), ES (n = 6), and combined RHES (n = 6 wounds). Daily wound images were segmented using an AI-assisted workflow: a U-Net (ResNet34 encoder, ImageNet-pretrained, trained on a parallel single-expert tracing study with held-out validation Dice = 0.906) generated initial boundary predictions, each reviewed and corrected as needed. Wound size measures (perimeter, area, equivalent diameter [D_eq], circularity, aspect ratio) were normalized to the day-0 value of each wound and analyzed by linear mixed-effects regression with mouse identity as a random intercept and mouse body weight as a covariate. On day 7, wounds were excised, fixed, processed for histology, and analyzed by Masson's trichrome (collagen content in granulation tissue) and GAP-43 immunohistochemistry (a marker of regenerative cellular activity). Results: All three treatments significantly accelerated wound closure compared to (-) (Day x Treatment interaction {chi}2(3) = 36.4, ***p < 0.0001). The closure-rate advantages on the log-D_eq scale were ES -0.047/day (***p < 0.0001), RHES -0.029/day (***p = 0.0005), and RH -0.022/day (**p = 0.0015). By day 7, mean D_eq had decreased to 0.58 of the day-0 value in ES, 0.69 in RHES, 0.73 in RH, and 0.79 in (-). Tissue analyses revealed treatment-specific differences in healing quality: RH and RHES wounds contained 6.1x and 8.5x more collagen in granulation tissue than (-) (both **p = 0.002 vs (-); both **p = 0.009 vs ES), and showed approximately 16x and 27x greater mean GAP-43 expression than (-), respectively; the RHES increase remained significant after Bonferroni correction (adjusted *p = 0.042), whereas the RH increase did not (adjusted p = 0.058). ES alone did not significantly increase either collagen content or GAP-43 expression. Wound shape was more circular and more stable across days in RH-containing groups. Mouse body weight did not predict closure, whereas image-derived dryness, eschar coverage, and wound contraction were significant negative predictors of measured wound size. Conclusion: ES, RH, and RHES each significantly improve wound closure kinetics. The improvement appears mechanistically distinct: ES principally accelerates closure rate, while RH principally enhances tissue-level regenerative markers (collagen deposition and GAP-43 expression). RHES combines both advantages.

Background: Three-dimensional tumor spheroids are an established radiobiology model, but scalable, reproducible readouts of dose-dependent radiation response are lacking. We evaluated whether optical coherence tomography (OCT) radiomics can quantify dose-associated response in spheroids, and how it compares with conventional brightfield morphology. Methods: This in vitro, cross-sectional study used SAS oral squamous cell carcinoma spheroids seeded at two densities (5000 and 10000 cells), irradiated at 0 to 12 Gy, and imaged on days 1 to 11 post-irradiation. Each OCT acquisition yielded co-registered structural-intensity and speckle-variance volumes. Radiomic features (shape, first-order, texture) were extracted with Radiomics.jl, filtered for repeatability, correlation-pruned, and ensemble-ranked. Dose correlation was assessed by repeated 5-fold cross-validation across five regressors, comparing brightfield-only (BF), OCT-only, and combined OCT+BF feature sets with paired Wilcoxon tests. Results: OCT-only models consistently outperformed the BF baseline (median R2 0.77 to 0.85 versus 0.61 to 0.69; p<0.001 for all regressors). Adding brightfield to OCT gave no consistent benefit, reaching significance only for Random Forest (p=0.026, power 0.62). A compact shared feature subset combined brightfield area dynamics with OCT texture, shape, and speckle-variance descriptors, all showing low repeat-scan variability relative to cohort variability. Conclusions: OCT radiomics provides a sensitive, reproducible, label-free high-throughput readout of spheroid radiation dose response that outperforms the current brightfield-based approach, without requiring concurrent brightfield acquisition.

Background. Breast cancer treatment depends on histopathological features, such as grade and receptor-defined subtype; however, specialist pathologist access is constrained when the workforce is limited. Commercial multimodal large language models (MLLMs) accept hematoxylin and eosin (H&E) image tiles through paid interfaces without local hardware or fine-tuning. However, prior pathology evaluations addressed only coarse tasks. Whether they reach treatment-determining accuracy and whether vendors agree remain unclear. Methods. We aimed to evaluate three vendor-designated flagship MLLMs (Claude Sonnet 4.6, Gemini 2.5 Pro, GPT-5.5) in 427 invasive breast cancer cases. Each case went to all three with identical H&E tiles and prompts, and the subtype was inferred in the second call. The reference was an institutional sign-out report of an immunohistochemistry-derived subtype. We calculated the concordance, sensitivity, specificity, Cohen's kappa, and pairwise McNemar and Bowker tests. Findings. Claude ranked highest by raw histologic-type concordance but lowest by kappa, classifying all 23 lobular and seven micropapillary carcinomas as invasive breast carcinoma of no special type. The models anchored the Nottingham grade to three modal grades. None of the models reliably identified human epidermal growth factor receptor 2-positive disease. The failure direction was vendor-specific: Claude and GPT-5.5 were under-detected, whereas Gemini was over-called. Twelve prompt variants (4,056 calls) did not recover sensitivity. Interpretation. No current commercial MLLM reaches deployment-ready accuracy for any treatment-determining feature of breast pathology. As each vendor fails in its own fixed direction, changing vendors alters the type of error rather than removing it; therefore, the value of these models is assistive rather than autonomous. At USD 0.20-0.50 per case, they may serve as supervised draft generators that leave the diagnosis with the pathologist.

Quantifying vascular architecture in histological whole slide images is needed to study tissue organisation, tumour microenvironment biology, and diseaseassociated vascular remodelling. However, vessel analysis in routine immunohistochemistry remains challenging. Available workflows are often manual, require programming expertise, or lack direct integration with digital pathology platforms. We developed VeSpA (Vessel Spatial Analysis), an open-source pipeline and QuPath extension for automated vessel segmentation and morphometric quantification in CD31-stained whole slide images. VeSpA combines configurable signal extraction, using CMYK Yellow channel extraction by default and optional DAB stain deconvolution for H-DAB images, with automatic or percentile-based thresholding, morphological refinement, contour filtering, and lumen filling to generate vessel masks from standard DAB-stained sections. The QuPath extension includes a graphical interface for selecting annotations, TMA cores, or whole images, configuring segmentation parameters, running the Python backend, and importing vessel objects directly into the QuPath hierarchy. For each detected vessel, VeSpA extracts area, major axis length, minor axis length, eccentricity, centroid, and orientation, while also appending summary measurements to parent annotations and TMA cores. Validation against independent pathologist annotations showed that VeSpA achieved segmentation performance close to inter-rater agreement and outperformed yellow channel prompt-based SAM and zero-shot YOLOv8-seg on overlap-based metrics in the tested dataset. VeSpA integrates vessel segmentation, morphometric feature extraction, and QuPath-based visualisation into a single reproducible workflow for vascular quantification in computational pathology and spatial analysis of histological tissue architecture.

Keloids are fibroproliferative skin disorders arising following dermal injury that extend beyond the original wound margins. Their pathogenesis remains poorly understood, and current treatments are associated with high recurrence rates. Identifying transcriptomic biomarkers that distinguish keloids from other skin and scar phenotypes may provide insight into disease mechanisms and facilitate the development of targeted therapeutic approaches. However, previous transcriptomic studies have often been limited by small sample sizes, pairwise comparisons between tissue classes, heterogeneous data-integration strategies, and a reliance on conventional differential gene expression (DGE) analysis. Here, we employed a multi-stage machine learning (ML) workflow for robust keloid biomarker discovery using transcriptomic datasets derived from both bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq). We assembled and harmonized, to the best of our knowledge, the largest curated cross-study keloid transcriptomic cohort currently available, comprising 81 samples from 13 independent studies spanning four clinically relevant tissue classes: normal skin, normotrophic scar, hypertrophic scar, and keloid scar. Through study-aware cross-validation, feature selection, partition-stability analysis, and bootstrap validation across multiple ML classifiers, we identified a panel of eight highly consistent biomarkers capable of distinguishing keloid from non-keloid samples. These biomarkers were associated with dysregulation of extracellular matrix homeostasis, fibrosis-resolution pathways, vascular remodelling, and metabolic reprogramming. Comparison with conventional DGE analysis demonstrated substantial agreement while also highlighting important differences between the two approaches. In particular, FASN was consistently identified by the ML workflow as an upregulated discriminatory biomarker despite exhibiting weak, non-significant differential expression in the DGE analysis. Cell-type-specific analysis further supported this finding, revealing significant FASN upregulation in fibroblast and vascular endothelial populations. These results demonstrate that ML and DGE capture complementary aspects of transcriptomic variation. This study provides a robust strategy for cross-study transcriptomic biomarker discovery and identifies candidate genes and pathways for future mechanistic and therapeutic investigation in keloids. 1 Author SummaryKeloids are abnormal scars that continue to grow beyond the original wound and can be difficult to treat because they frequently recur after therapy. Although many studies have investigated the biology of keloids, the molecular mechanisms that distinguish them from other scar types remain incompletely understood. Identifying biomarkers involved in keloid formation may help inform improved treatment strategies. Previous transcriptomic studies have often been limited by small sample sizes and inconsistent analytical approaches. In this study, we combined gene-expression data from multiple independent studies to create, to the best of our knowledge, the largest cross-study transcriptomic collection available for keloid analysis. We then applied several machine learning approaches to identify genes that consistently distinguished keloids from other skin and scar phenotypes. The identified biomarkers were associated with extracellular matrix remodeling, fibrosis, vascular function, and cellular metabolism. One gene involved in fatty-acid synthesis, FASN, was repeatedly identified by the machine learning analyses despite being overlooked by conventional gene-expression methods. Additional single-cell analyses confirmed elevated FASN expression in specific cell populations within keloid tissue. More broadly, this work provides a strategy for discovering robust biomarkers from heterogeneous biological datasets and identifies molecular targets for future studies of keloid disease.

Introduction Conjunctival melanoma (CM) is a rare cancer with a potentially high recurrence rate. The mechanics of its progression, its relationship with neighboring tissues, and its molecular characteristics are largely unknown. Diagnosis currently requires a biopsy and the time and expertise of a pathologist. Methods Archived human biopsies containing CM were submitted to Xenium spatial transcriptomic analysis. Regions were graded by disease progression through histopathology. Differential expression (DE) and composition analysis were performed across disease states. Results From three patients, 12 formalin-fixed paraffin-embedded (FFPE) tissue specimens were recovered. Composition analysis showed that melanoma depletes fibroblast and epithelial cells while melanocytes proliferate. DE signatures specific to each state show a clear pattern of progression from inflammation, to cellular restructuring, and then to tumor progression and malignancy. Conclusion Spatial transcriptomics allows single-cell transcriptomics techniques to compare spatially relevant annotations that are difficult to separate by library. This study proposes disease progression biomarker candidates that may elucidate the mechanics of CM progression and function as objective diagnostic and prognostic tools in the future.

Human skin colors occupy a characteristic banana-shaped region in CIE L*a*b* space, but why skin color coordinates are restricted to this region and how they relate to melanin and blood remain incompletely understood. We developed a physics-based framework linking skin chromophore content to colorimeter-derived skin color coordinates using two complementary three-layer light transport models. Across physiologic ranges of epidermal melanosome volume fraction and dermal blood volume fraction, simulated reflectance spectra were converted to CIE L*a*b* coordinates and compared with human skin color measurements from the International Skin Spectra Archive. Physiologic variation in melanin and blood reproduced the observed banana-shaped locus and revealed distinct chromophore-specific trajectories. Iso-melanin trajectories became progressively more linear as melanin increased, whereas iso-blood trajectories retained the curvature of the skin color locus. As melanin increased, perceptible color differences from blood volume changes were reduced, providing a mechanistic explanation for reduced erythema visibility in highly pigmented skin. These relationships were stable across plausible variations in layer thickness and tissue oxygenation and agreed with external validation data. The framework also identified when the Individual Typology Angle is confounded by blood or distorted by dermal melanin. Together, these findings establish a mechanistic optical basis for interpreting colorimeter-derived skin color coordinates.

An autocrine pro-adhesive/pro-contractile signaling loop, through the mechanosensitive transcriptional cofactor YAP, promotes fibrosis. The CCN family of matricellular proteins modify adhesive signaling. Of these, CCN3 is antifibrotic. We show that BLR-200, a CCN3-derived peptide, has anti-fibrotic properties in the bleomycin-induced model of scleroderma skin fibrosis. In vitro, BLR-200 delayed, but did not abolish, fibroblast adhesion to collagen and nuclear YAP localization. In vivo, BLR-200 prevented/treated bleomycin-induced skin fibrosis, and reduced bleomycin-induced expression of profibrotic genes including alpha-smooth muscle actin, CCN1 and CCN2. Lineage tracing and scRNA-seq analyses revealed that the myofibroblasts in this model were quantitatively derived from collagen-lineage Pi16+/Col15+ve fibroblasts. BLR-200 prevented myofibroblast differentiation in this model and trajectory of fibroblasts toward a Sfrp2-positive subset, a cell type associated with poor clinical outcome. BLR-200 impairs YAP activation in vitro and appearance of translationally-relevant fibroblast subtypes in vivo and is a novel anti-fibrotic agent for SSc skin fibrosis.

The innate immune system controls bacterial growth and modulates inflammation during wound healing. TCP-25 is a synthetic thrombin-derived host-defense peptide that combines direct antibacterial activity with neutralization of microbial products and modulation of CD14-dependent inflammatory signaling. We investigated whether this dual mechanism translates to human wounds using longitudinal samples from 24 healthy volunteers enrolled in a randomized, double-blind, within-participant, placebo-controlled phase I dose-escalation study of topical TCP-25 gel in matched epidermal suction blister wounds. We assessed inflammatory cytokines, neutrophil-derived proteins, wound exudation, cultivable bacterial burden, spatial bacterial distribution, and microbiome composition. TCP-25 reduced multiple cytokines, myeloperoxidase, and heparin-binding protein, with the strongest effects observed during the peak inflammatory phase. These changes were accompanied by reduced wound exudation and significant reductions in cultivable bacterial burden. Despite this antibacterial effect, microbiome composition and diversity remained largely unchanged, and participant-specific microbial profiles were preserved. TCP-25 therefore coordinated bacterial control, modulation of the physiological inflammatory response, and reduced wound leakage without major disruption of the resident microbiota composition. These findings provide clinical support for translating nature's endogenous host-defense principles into new therapies for complex wounds.

Germline pathogenic or likely pathogenic variants (GPVs) in BRCA-1 Associated Protein 1 (BAP1) are associated with a spectrum of tumors, including uveal melanoma (UM). Currently, UM patients with BAP1 GPVs are treated as high-risk class 2 tumors based on mostly empiric data. In the current study, we examined the clinical phenotype of a cohort of 29 UM patients with BAP1 GPVs. We also carried out a systematic review of the literature of UM patients with BAP1 GPVs. We observed that UM patients with BAP1 GPVs have significantly lower median age of diagnosis compared to median age reported in UM patients in the Surveillance, Epidemiology, and End Results Program (SEERS) database. Metastatic risk and overall survival in the UM BAP1 GPVs cohort were statistically significant from those in patients with class 1 tumors, but were comparable to those observed in UM patients with class 2 tumors. In UM BAP1 GPVs treated with radiation (n=12), no secondary cancers were observed in the field of radiation in a median 26.5 months (range, 4-119 months) follow up period. One patient experienced a separate growth of UM at a distinct location within the same eye. These data support managing UM in patients with BAP1 GPVs as aggressive class 2 tumors, following the currently established standard of care for these high-risk tumors.

Plasma proteins are promising biomarkers and potential drug targets in psoriasis. We conducted a two-sample Mendelian randomisation analysis integrating protein quantitative trait loci from UK Biobank and deCODE genetics with a psoriasis GWAS meta-analysis of 36,466 cases. To strengthen causal inference, we performed colocalisation analyses to evaluate shared genetic signals and applied summary data-based MR (SMR) with HEIDI testing using expression quantitative trait loci to exclude linkage-driven associations. After correction for multiple testing, 78 circulating proteins showed genetically predicted associations with psoriasis, with 27 demonstrating strong colocalisation (PPH4>80%). Triangulation prioritised 12 Tier 1 proteins, STX4, FLT3, NFKB1, IL18, PRSS53, SPAG1, SGSH, PLAT, RALB, TNFSF11, SPHK2, and STAT3, supported by consistent effects and no heterogeneity. Network profiling and Genome for REPositioning analyses assessed biological connectivity and druggability, revealing enrichment in anatomical therapeutic chemical groups L and B. Single-cell RNA sequencing confirmed cell-type-specific expression and modulation following IL-23 blockade.