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This study reported that dandelion herb-derived carbon dots significantly enhanced wound healing in mice with Staphylococcus aureus infections, outperforming a commercial wound healing spray through their antibacterial and dual ROS-modulating capabilities.

The authors of this study developed a novel CNN architecture aimed at improving detection of Alopecia Areata through image-based datasets, achieving a top accuracy of 98% compared to four other machine learning models.

In this study, the researchers used machine learning techniques on an image dataset to diagnose Alopecia Areata, achieving a maximum accuracy of 98.3%.

This article discusses highlights from the 2019 Dermatology Nurses' Association's annual meeting, covering various dermatological conditions and treatments, and reports no new clinical findings.

This study found that adapalene-loaded nanospheres in a hyaluronic acid gel enhanced skin penetration and were nonirritant, making them potentially suitable for treating acne on oily skin.

This study investigated NNAT expression in embryonic and postnatal rat tissues, finding its localization in both undifferentiated and differentiated cells across tissues such as the pancreas, tongue, and testis.

In this study, a newly designed protein degrader targeting androgen receptors showed promise in reversing hair regrowth inhibition in a mouse model of androgenetic alopecia, suggesting potential as a novel and safe treatment strategy.

This study found that MSN-ceria nanomaterial accelerates cutaneous wound healing in rat models by reducing ROS levels and promoting collagen deposition, leading to improved tissue regeneration without significant scarring.

This study found that GoogLeNet outperformed other CNN models in accurately identifying the type of folliculitis.

The Ewha Medical Journal is now in PubMed, has an AI article editor, and offers Korean reporting guidelines.

A deep learning model accurately detects early hair loss signs using scalp images.

This study introduced a novel deep clustering approach for melanoma detection from dermoscopic images, demonstrating improved performance over existing methods by mitigating class imbalance issues using a center-oriented margin-free triplet loss.

In this case report, a 7-month-old boy with Netherton syndrome experienced significant improvement in symptoms, including reduced pruritus and increased hair growth, through a combination of intravenous immunoglobulin and dupilumab treatment, which also decreased high serum IgE levels and food-specific IgE antibodies.

This study developed a deep-learning model that accurately diagnosed alopecia areata with an accuracy of 88.92% and distinguished its activity levels with an accuracy of 83.33%, highlighting the potential for artificial intelligence in improving the diagnosis and treatment of this autoimmune hair loss condition.

This study reported that a new deep learning algorithm using Mask R-CNN improved hair follicle classification accuracy by 4 to 15%, suggesting potential clinical application for enhanced hair loss diagnosis.

This study formulated and characterized a dutasteride-loaded nanocrystalline suspension for long-acting parenteral delivery, finding that it provided sustained drug release in rats with a significant reduction in local inflammation over 28 days following intramuscular injection.

This study developed a dissolvable microneedle system delivering specific molecules to remodel lymphatic networks and normalize metabolic processes, which accelerated hair growth and activated hair follicle stem cells in a mouse model of androgenetic alopecia.

This study identified altered mRNA and lncRNA profiles in NS scalp tissues, highlighting CDKN2AIP as a downregulated gene involved in a ceRNA network.

In this study, a deep neural network model called regX was developed to prioritize driver regulators for cell state transitions by incorporating gene-level regulation and interactions, showing potential therapeutic targets in type 2 diabetes and hair follicle development when applied to single-cell multi-omics data.

Reducing neutrophils or inhibiting NETs improves wound healing in sickle cell disease.

This study found that the WNMFDDA model effectively predicts drug-disease associations, achieving high accuracy in cross-validation and confirming most candidate associations through existing databases.

This publication compiles abstracts from the 19th Annual Fall Meeting of the Sexual Medicine Society of North America, highlighting advancements and discussions in various areas of sexual medicine without reporting new research results.

This study established a standardized in-vitro 3D skin model using adult diseased skin cells to investigate the underlying mechanisms of small fiber neuropathies, providing a foundation for further research into their pathophysiology.

This study found that concentrated nanofat, used alone or with decellularized nanofat, may enhance hair growth in mice by activating dermal papilla cells and the anagen phase.