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This study found that among patients with Down syndrome, those with alopecia areata may have increased antiperoxidase antibodies, possibly linked to hypothyroidism.

This study found that in patients with severe alopecia areata, those who responded early to baricitinib treatment typically had a lower baseline Severity of Alopecia Tool score, shorter disease duration, and higher erythrocyte sedimentation rate, suggesting these factors may predict therapeutic success.

This study found that patients with alopecia areata had a significantly higher mean platelet volume compared to healthy individuals, suggesting a potential link between hematological markers and the severity of the disease.

This study explored biochemical biomarkers in post-COVID-19 patients experiencing acute telogen effluvium, finding sex differences in blood characteristics and varying D-dimer levels by age, with elevated D-dimer showing correlations with inflammation markers.

In this randomized trial, lupus patients taking daily 200 μg selenium supplements for eight weeks showed significant improvements in metabolic markers like CRP, ESR, MDA, and GPX, as well as reduced clinical symptoms such as arthritis and alopecia, compared to those receiving a placebo.

This study found that patients with alopecia areata had higher levels of ESR, CRP, and mean platelet volume compared to controls, and that these markers, along with the neutrophils to lymphocytes ratio, were associated with increased disease severity.

This case report describes a 17-year-old female patient diagnosed with systemic lupus erythematosus, presenting with arthralgia, hair loss, and Raynaud's phenomenon. The diagnosis was supported by elevated ESR and positive autoantibodies, and treatment included hydroxychloroquine and prednisone.

This study found that lower GPX4 mRNA levels in polymorphonuclear neutrophils of systemic lupus erythematosus patients were negatively associated with disease activity and serological markers, suggesting a diagnostic value for GPX4 mRNA.

This study found that patients with alopecia areata had altered levels of inflammatory and coagulation markers, suggesting an association with disease pathogenesis and potential predictive value.

This descriptive study reported that Chronic Cutaneous Lupus Erythematosus was the most prevalent subtype, highlighting distinct clinical and pathological features among Cutaneous Lupus Erythematosus subtypes.

A 54-year-old man with painful skin blisters and fever was diagnosed with Sweet syndrome and successfully treated with corticosteroids.

This study found that Chinese medicine treatment "Tonifying Kidney and Removing toxins" significantly improved clinical symptoms and reduced disease activity in patients with systemic lupus erythematosus compared to controls.

This study determined that the incidence of Discoid Lupus Erythematosus at the Government General Hospital, Chennai, from 2006 to 2008 was 1.7 per 1000, with localized and disseminated forms manifesting distinctive demographic and clinical patterns.

This study concluded that patients with androgenetic alopecia may have a higher risk of cardiovascular diseases compared to people without this condition.

This study presents a new automated computer vision system to objectively measure periocular hair density changes in breast cancer patients undergoing chemotherapy, demonstrating high precision in tracking individual changes and potential as a reliable tool for future clinical trials.

This study introduces ALUDWIG, an automated tool for assessing female androgenic alopecia severity from smartphone images, which may offer a more consistent alternative to current scoring methods like the Ludwig scale.

A new image-based method improves accuracy in measuring hair loss in mice.

This study observed that systemic lupus erythematosus may not be as uncommon among African Blacks as previously reported, highlighting the need for early aggressive treatment.

This study identified that certain diseases, including AIDS and systemic lupus erythematosus, may cause African hair to change to a silky, wavy texture similar to neonatal hair in affected patients.

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 article reviews recent advancements in forensic hair testing, emphasizing its growing use for detecting past substance exposure, identifying emerging trends like micro-segmentation and hair scanning, and proposing standardized procedures to improve reliability and application in forensic toxicology.

In this study, the researchers reported that their novel algorithm for hair restoration in dermoscopy images achieved high accuracy and texture preservation, outperforming other techniques in diagnostic accuracy and texture quality measures.

This study presents a new hair removal algorithm for dermatoscopic images of skin lesions that improves hair detection accuracy by 2–7% and hair repair accuracy by 2–5% on average, using advanced techniques like maximum variance fuzzy clustering, Criminisi priorities, and the ant colony algorithm.

This review examines the current state of automated vitiligo detection systems, noting a lack of large, diverse datasets and consistent imaging conditions, while comparing traditional and modern machine learning approaches to improve reliability and applicability.

This study found that administering spironolactone or canrenone to castrated male rats significantly decreased the availability of cytoplasmic androgen receptor binding sites, suggesting canrenone mediates spironolactone's antiandrogenic effects in skin.

This review provides an overview of Hox genes, focusing on their evolutionary history, genomic organization, and roles in development, but reports no new study results.

This study found that crossbred lambs fed liquid diets with reconstituted cow's milk initially grew wool without crimp, with crimp resuming two weeks post-weaning.

This review examines the use of computer vision techniques, specifically deep learning architectures and image processing algorithms, for detecting and assessing skin conditions like vitiligo and dermatitis, and highlights the need for disease-specific datasets to improve automated diagnostic tools in dermatology.

This study evaluates a framework using neural networks and machine learning techniques to classify and detect Alopecia Areata from hair images, aiming for accurate differentiation between healthy hair and the condition.

This study proposes a new mathematical model, the Harmonic Mean equation, for precisely quantifying nuclear pleomorphism in breast cancer grading, showing high performance with accuracy, recall, specificity, precision, and F1-score metrics.