Results 181 to 190 of about 71,720 (316)

Assessment of bactericidal activity of some lichen extracts by disc diffusion assay

open access: yes, 2017
In the presented study, thirty-two natural extracts obtained from lichen species; P. reticulatum, P. tinctorum, Herpothallon sp., H. leucomelos, R. celastri, Leptogium sp. and P. crinitum, were evaluated for their bactericidal activity against three gram
Hengameh, Parizadeh, Rajkumar, G. H.
core  

S3 guideline diagnostics and therapy of alopecia areata – Part 1: Diagnostics and epidemiology

open access: yesJDDG: Journal der Deutschen Dermatologischen Gesellschaft, EarlyView.
Summary In the project funded by the Innovation Committee at the G‐BA, the S3 guideline for the diagnosis and treatment of AA was developed between 2023 and 2025. The interdisciplinary expert panel consisted of representatives from the German Dermatological Society, in particular from the Pediatric Dermatology Working Group, the Professional ...
Ulrike Blume‐Peytavi   +13 more
wiley   +1 more source

Zosteriform Lichen Planus. [PDF]

open access: yesClin Case Rep
Jaiswal S   +4 more
europepmc   +1 more source

Ectopic Adipocytes in Scarring Alopecias: Comparison With Normal Scalp and Potential Therapeutic Implications

open access: yes
Journal of Cutaneous Pathology, EarlyView.
Annelise de Almeida Verdolin   +4 more
wiley   +1 more source

Phenotypes and clinical outcomes in children with moderate‐to‐severe atopic dermatitis across diverse ancestries: a Spanish multicenter observational study and cluster analysis (AD‐SKINS Project)

open access: yesJDDG: Journal der Deutschen Dermatologischen Gesellschaft, EarlyView.
Summary Background and Objectives Atopic dermatitis (AD) has a highly variable clinical phenotype and ancestry can contribute to this heterogeneity. This study aims to identify clinical phenotypes of AD in children from diverse ancestry groups, evaluate clinical outcomes and response to treatment, and define phenotypic clusters with potential relevance.
Eugeni Prat‐Colilles   +21 more
wiley   +1 more source

Multiclass convolutional neural network vs. 96 dermatologists in skin lesion diagnosis, an international study

open access: yesJDDG: Journal der Deutschen Dermatologischen Gesellschaft, EarlyView.
Summary Background and objectives Artificial intelligence was shown to improve diagnostic accuracy for skin cancer detection. While most clinically approved models provide binary “benign/malignant” classifications, multiclass predictions may offer greater clinical utility.
Katharina Susanne Kommoss   +11 more
wiley   +1 more source

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