research Prioritizing Susceptibility Genes for the Prognosis of Male-pattern Baldness with Transcriptome-wide Association Study
The research identified genes linked to male-pattern baldness and potential drug targets for treatment.
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research Genotyping of the rs1800440 Polymorphism in CYP1B1 Gene and the rs9258883 Polymorphism in HLA-B Gene in a Spanish Cohort of 223 Patients with Frontal Fibrosing Alopecia
Certain genetic variants are linked to frontal fibrosing alopecia in Spanish patients.
research Postzygotic Mutations in Beta-Actin Are Associated with Becker’s Nevus and Becker’s Nevus Syndrome
Mutations in the ACTB gene cause Becker’s nevi and may lead to muscle issues in Becker’s nevus syndrome.
research Machine Learning Approach for Predicting Systemic Lupus Erythematosus in Oman-based Cohort
The machine learning model accurately predicts Systemic Lupus Erythematosus in Omani patients.
research Asymmetric adhesive SIS-based wound dressings for therapeutically targeting wound repair
The new wound dressing improves healing and tissue repair better than conventional dressings.
research Sodium pentaborate pentahydrate promotes hair growth through the Wnt/β-catenin pathway and growth factors
Sodium pentaborate pentahydrate can increase hair growth and improve hair quality at certain doses.
research Studies on basal cell carcinoma with emphasis on the role of the human homologue of the Drosophila patched gene
PTCH gene mutations contribute to basal cell carcinoma development.
research Assessment of efficacy of different botulinum toxin A concentrations in the treatment of androgenetic alopecia assessed by dermoscopy
Higher concentration of botulinum toxin A is safe and effective for treating hair loss in men and women.
research Differential distribution and genetic determination of eccrine sweat glands and hair follicles in the volar skin of C57BL/6 mice and SD rats
C57BL/6 mice and SD rats have different sweat gland and hair follicle patterns, useful for skin research.
research LB1040 Machine learning-based predictive model with routine blood work identifies moderate-severe alopecia areata
Machine learning can use blood tests to help predict moderate-to-severe alopecia areata.