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This review discusses the chemical stability of protein envelopes found in the epidermis and other stratified squamous epithelia, but reports no new clinical results.

This review discusses recent advances in noninvasive hair imaging technologies, such as global photography, trichoscopy, reflectance confocal microscopy, and optical coherence tomography, highlighting their potential to improve hair diagnostics and treatment monitoring, while also outlining their clinical applications and limitations.

This study developed BroadAMP-GPT, a computational-experimental framework, to discover new antimicrobial peptides, identifying candidates effective against multidrug-resistant pathogens. Notably, AMP_S13 showed strong stability, low toxicity, and efficacy in infection models, highlighting the platform's potential in combating antimicrobial resistance.

In this study, researchers developed a machine learning model that accurately diagnosed scalp conditions like fine dandruff and perifollicular erythema with 75% and 82% accuracy, respectively, and created a user-friendly web platform for scalp health self-assessment, which achieved high user satisfaction.

In a rare case described by this source, a woman in her thirties was diagnosed with primary essential cutis verticis gyrata, a condition marked by thick scalp folds, after secondary causes were ruled out through clinical evaluations and biopsy.

A new computer tool quickly measures hair thickness differences in people with common types of hair loss.

This study developed a hat-shaped device with wearable sensors to estimate scalp moisture content using machine learning, demonstrating that it can provide accurate measurements comparable to professional scalp analyzers without the need for high-cost equipment.

This study found that their newly developed ADRL framework significantly improved the accuracy of scalp tissue layer segmentation in HR-MR images compared to existing methods.

In this study, researchers developed a deep learning model that efficiently classifies five degrees of harm with high accuracy, achieving up to 98% precision, recall, and F1-score across various harm levels, indicating strong potential for practical application in automated harm evaluation.

This study reports that oxytocin receptor expression in keratinocytes shows a potential relationship with touch sensory neurons, suggesting a role in skin sensitivity and the broader function of sensory neurons.

In this study, a machine-learning model was evaluated for its ability to categorize various hair conditions, achieving high accuracy and balance between precision and recall, with an overall accuracy of 97% in detecting hair problems.

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 study's model suggests that low androgen levels can increase selection for prostate cancer phenotypes resistant to hormonal therapy, potentially leading to more aggressive forms of cancer.

This paper proposes that acne vulgaris is a transient inflammatory response during adolescence due to changes in facial skin's microbiota and sebum environment rather than a stable skin condition.

This review examines the role of skin microbes in enhancing the skin barrier and their involvement in skin diseases like atopic dermatitis, while also discussing current and future therapeutic strategies targeting the skin microbiome.

This review discusses drug repurposing strategies for rare diseases, highlighting methodologies, achievements, and challenges, but reports no new clinical results.

This study supports the traditional use of T. procumbens for diabetes treatment, showing improvements in body weight and glucose tolerance with no toxicity signs in normal rats.

This paper reviews AI integration in robotic surgical systems, highlighting enhanced precision and reduced fatigue but noting challenges like high costs and ethical concerns, suggesting responsible adoption to realize potential benefits for surgical care.

This review summarizes advancements in forensic DNA phenotyping for appearance, ancestry, and age prediction from crime scene samples, reporting no new research findings but highlighting areas needing further research and validation.

In this study, researchers evaluated various machine learning models for predicting type 2 diabetes risk, finding that Random Forest and K-NN models performed best in terms of precision, recall, accuracy, and other metrics using common symptoms as features.

This study reports that emotion recognition technology integrated with intelligent devices is advancing applications to support emotion recognition and interventions, though further research is needed for effective use in dynamic or complex environments.

This study found that women's biomedical patents more often focus on women's health needs, highlighting how inventor representation can influence the diversity of inventions.

This study found that artificial intelligence assistance improved diagnostic accuracy in dermatologic cases for primary care physicians and nurse practitioners, with higher agreement rates with reference diagnoses observed.

This study proposes an AI-based method, DRGCC, using GraphSAGE and clustering constraints to predict associations between drugs and diseases, demonstrating reliable predictive performance that may aid drug repositioning efforts, including exploring drugs for COVID-19 treatment.

This study systematically examines how smart biomaterials used with DLP technology can enhance bioprinting in tissue engineering and regenerative medicine, while also identifying current challenges and future research needs.

This case study reports a 70-year-old man with treatment-resistant pityriasis rubra pilaris achieving complete clinical remission with ustekinumab, adding to evidence supporting biologic therapy when TNF inhibitors are unsuitable.

In this study, researchers observed a dose-dependent occurrence of persistent radiation-induced alopecia in patients with primary CNS tumors or head and neck sarcomas, noting distinctive patterns and features, and suggesting potential benefits of topical minoxidil and procedural interventions for treatment.

Keratin structure changes during keratinization, but the exact model remains uncertain.

This study explored the role of AI technologies in plastic and reconstructive surgery, highlighting their potential across preoperative, intraoperative, and postoperative stages, while also identifying challenges like data privacy and regulatory issues that must be addressed for successful implementation.