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This study developed a new neural network model (AA-GAN-AB-MTEDeep) to enhance Alopecia Areata classification using synthetic scalp images, achieving an accuracy of 96.94%.

This review reports that while deep learning shows promise in diagnosing scalp disorders from images, challenges remain with data quality and model interpretability, suggesting that integrating explainable AI techniques is crucial for building trust and facilitating clinical adoption.

This study found that long non-coding RNAs are differentially expressed in androgenetic alopecia, suggesting potential roles in its development and novel targets for prevention and treatment.

This study developed a deep-learning model using unannotated dermatology images from online forums, achieving 49.64% accuracy in classifying 22 skin diseases and 61.76% accuracy in detecting monkeypox, highlighting the potential of these images for skin disease diagnostics in China.

In this study, the authors found that applying hypobaric pressure to the skin significantly increases the transdermal permeation of large molecules by enhancing diffusion, despite the associated skin stretching and hair follicle enlargement not fully explaining this effect.

Innovative methods are reducing animal testing and improving biomedical research.

This study found that white hair fibers have lower lipid content and different water absorption dynamics compared to brown hair fibers, suggesting differences in their barrier functions.

This review discusses the role of hair follicle bacterial colonization in immune responses and the pathogenesis of alopecia but reports no new clinical results.

In this study, a mixture of tocopherol acetate, L-menthol, and stevioside was more effective in promoting hair growth in mice compared to tocopherol acetate or L-menthol alone.

In this narrative review, the authors highlighted that AI-supported electronic health record analysis could help recognize Polycystic Ovary Syndrome/Polyendocrine Metabolic Ovarian Syndrome earlier, but also warned that these systems might perpetuate historical biases if not properly validated and interpreted.

This study used integrated single-cell chromatin and transcriptomic analyses in developing mouse skin to uncover gene networks involved in skin lineage specification and identified Mef2c+ upper fibroblasts as potential precursors to certain muscle-like structures, with cross-species findings in human skin.

This study reports that the ScalpEye system accurately diagnosed dandruff, folliculitis, hair loss, and oily hair with a precision range of 97.41% to 99.09%.

This study demonstrated that a CNN-based model using VGG-16 architecture achieved a 94.5% accuracy in classifying ten types of hair diseases, implying a promising tool for aiding health professionals in diagnosing hair conditions accurately.

In this study, researchers developed a method to create a synthetic dataset of facial acne images using generative techniques, achieving 97.6% classification accuracy with InceptionResNetv2, which helps overcome privacy concerns in biomedical applications by using anonymized data.

This study found that miRNAs increase and target mRNAs and lncRNAs decrease from the anagen to telogen phase in mouse hair follicles, and these ceRNA networks may play a role in hair follicle cycling.

This study used bibliometric analysis to evaluate global research on AI applications in dermatology, identifying 406 relevant papers and highlighting current priorities such as machine learning for wound progression, AI in teledermatology, and applications for skin diseases.

This study found that miR-432 inhibits KRT83 expression, revealing potential molecular mechanisms for the formation of curly fleece in Tan sheep and suggesting implications for understanding curly hair formation in humans.

In this study using the C3H/HeJ mouse model of alopecia areata, researchers found that hyperexpanded CD8⁺ T cell clones were sufficient to initiate disease, establishing a causal link between T cell clonality and pathogenicity.

This historical analysis highlights the pioneering contributions of several late 19th-century Jagiellonian University professors to Polish and European medicine, including advancements in craniotomy, urology, and gastroscopic techniques, as well as clinical use of nitroglycerin and early identification of coronary artery embolism.

This study explored the expression and potential functions of long non-coding RNAs in the skin pigmentation of Koi carp, revealing their involvement in pigmentation and differentiation mechanisms.

This study presents iSiMPRe, a method identifying protein regions enriched in mutations, revealing potential cancer-related genes and enhancing understanding of mutation effects across a wide range of cancer types.

This study demonstrated that current facial recognition software can accurately identify individuals from MRI head scans within minutes, highlighting significant privacy concerns for clinical trial participants and the need for enhanced data protection measures.

This study revealed that BMP5 in onychofibroblasts may play a key role in the differentiation of nail matrix keratinocytes, highlighting transcriptional similarities between nail and hair structures.

In this study, researchers found that during zebrafish telencephalon regeneration, the lesioned hemisphere showed distinct gene expression changes and activated Wnt/β-catenin signaling early after injury, suggesting this pathway's significant role in recovery.

This bibliometric analysis identified SGK1 as a key factor in cancer, showing that its dysregulation can lead to tumor growth and treatment resistance. The authors highlighted SGK1's potential as a therapeutic target, but note that further research is needed to develop effective treatment strategies.

This bibliometric analysis reviewed 4,515 articles on strabismus research from 2004 to 2023, highlighting a shift towards innovative and interdisciplinary treatment methods, with significant contributions noted from the USA, China, and the UK.

In this study, the researchers found that rare genetic variants make a minor contribution to male-pattern hair loss risk, identifying five significant gene associations, including novel genes, and noting a shared basis with monogenic hair loss disorders.

This study found that hair mass index can effectively link hair productivity with clinical scalp coverage perception, suggesting its potential usefulness in diagnosing hair loss patterns and responses to treatment.

This study found that root hair length and density in rice are controlled by distinct genomic regions, with 18 regions identified but no overlap between the traits.

This study established an animal model using UV-irradiated C57BL/6 mice to assess hair luster, reporting that UV exposure alters keratin-associated protein gene expression, and suggested potential for developing effective hair care products by evaluating treatments like oral minoxidil.