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This study suggests that nestin is an important marker for identifying HMB-45-negative cells in nodular melanomas, particularly in the dermal parts.

This paper discusses forensic DNA phenotyping, emphasizing its ability to infer visible traits from biological samples without reference samples, but notes ethical and legal concerns related to its use.

This study analyzed the genetics of the patchiness phenotype in New Zealand rabbits and found that the gene KRT82, with identified SNPs in its promoter, may serve as a potential biomarker for breeding these rabbits.

This study identified molecular differences between dysplastic nevi and common melanocytic nevi, including altered keratinocyte differentiation, increased hair follicle-related molecule expression, and distinct immune microenvironment characteristics in dysplastic nevi.

This study found that tissue transcriptomics and a normalization approach can effectively cluster nine inflammatory skin diseases and identify specific biomarkers, including PTEN as a marker for cutaneous lupus erythematosus.

This study developed a new method for analyzing multivariate time-series data that successfully predicts website competition dynamics and outperforms conventional methods in identifying and predicting competitive structures.

This study found that a genetic model using SNPs can predict early-onset male-pattern baldness with moderate accuracy, which may assist in decisions about interventions.

This study identified four keratin genes associated with hair follicle development that were expressed more highly in super fine wool Xinji sheep compared to fine wool sheep.

This study concluded that the KNPs@M/G microneedle system offers a promising strategy for treating radiation-induced skin injury by promoting antioxidative, anti-inflammatory, and regenerative effects.

This study identified four immune-related signaling molecules (LGR5, PTN, JAG1, and DKK1) associated with keloid, suggesting their potential role in its pathogenesis and as targets for new treatments.

This study found that mutations in certain keratin genes significantly affect wool traits in Chinese Merino sheep, suggesting these genes could be important for sheep breeding to improve wool quality.

This study found that an automated tumor-infiltrating lymphocyte classification algorithm identified thin melanomas with less immune response, which were associated with higher mortality compared to other cases in the study.

In this study, the BaldGraphFormer framework, integrating visual and clinical data, outperformed unimodal baselines in early-stage androgenetic alopecia detection, achieving an F1-score of 97.62% and macro-average AUC of 0.992, suggesting its potential to support dermatological decision-making and early intervention.

This study suggests that estimating autism likelihood as early as one month after birth may enable more precise early intervention for children with developmental support needs, potentially improving diagnosis, workflows, and reducing service wait times.

This study reviews methods to ensure the reliability of machine learning models in medical imaging, focusing on bias detection, data drift assessment, and accuracy estimation without ground truth labels to enhance integration into clinical settings.

This study analyzed blood samples from individuals with alopecia areata and found that NKG2D+ immune cells, particularly memory-like NK cells, may better correlate with disease activity compared to CD8+ cells, though significant variability among individuals complicates these findings.

This study identified 53 keratins in the yak genome, predicting diverse phosphorylation sites and subcellular localizations, and highlighted strong gene expression correlations during the yak hair follicle development cycle.

In this study, machine learning models showed high accuracy in predicting therapeutic outcomes for female pattern hair loss, highlighting the significant impact of age of onset and condition duration on treatment response.

This study found that nestin-expressing progenitor cells, capable of becoming ORS keratinocytes, are present in both developing and adult mouse hair follicles.

This study found that the HairComb algorithm achieved high accuracy in quantifying percentage hair loss across various types of alopecia, suggesting its potential for standardized automated assessments.

This study found that systemic treatment with DS77754007, a KLK5 inhibitor, improved skin symptoms in a mouse model of Netherton Syndrome more effectively than certain antibody treatments, suggesting KLK5 inhibition as a promising therapeutic approach for this condition.

This study investigated the roles of long non-coding RNAs in mouse hair follicle stem cells, using sequencing to identify potential biomarkers and targets for treatments in both mice and humans.

In this study, improved hidden Markov algorithms based on Bayesian methods enhanced the resolution and segmentation accuracy of low-dose CT images significantly more than naive Bayesian methods.

This research identified K31 as a new marker for distinguishing clear secretory cells in human eccrine sweat glands, aiding in differentiating between distinct cell types within these glands.

This study found that a pre-trained image processing technique accurately classified scalp conditions with 85% accuracy, suggesting potential for automated diagnosis and treatment selection.

This study presents a computational approach, CATNIP, which repurposes drugs using only their biological and chemical information, predicting new uses like adrenergic uptake inhibitors for Parkinson's and vandetanib for Type 2 Diabetes.

This study highlights that early detection and tailored treatment based on kidney biopsy classification are crucial in managing lupus nephritis to prevent progression to end-stage kidney disease, with a focus on saving nephron cells.

This study found that single-nucleus RNA sequencing identified more relevant keratinocyte clusters and specific markers than single-cell RNA sequencing, offering a new perspective on skin cell differentiation and function.

In this study, researchers identified specific gene polymorphisms in Subo Merino sheep that significantly affect wool traits, suggesting these genetic markers could aid in breeding high-quality fine-wool sheep.