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This article presents guidelines developed by a multidisciplinary expert panel for the care of adolescent transgender and non-binary individuals with gender dysphoria, emphasizing individualized, affirmative care to enhance well-being and quality of life.

This commentary described developing a framework to evaluate how pharmacists in community pharmacy care clinics impact emergency department visits, focusing on conditions they can manage, adverse medication events, and necessary referrals.

This study established consensus criteria for classifying alopecia areata severity, aiding clinicians in accurate diagnosis and treatment planning.

This study introduces "Homeodynamic Rejuvenation" as a method to restore the skin's resilience by enhancing its ability to detect and recover from stress, focusing on five core biological processes critical for maintaining skin function and health amidst environmental and metabolic challenges.

This article proposes a classification for small graft transplants that includes technical factors to improve communication and facilitate comparative studies, reporting no new clinical results.

This study presents a computational approach, CATNIP, which repurposes drugs using only their biological and chemical information, predicting new uses like adrenergic uptake inhibitors for Parkinson's and vandetanib for Type 2 Diabetes.

This study identified a four-gene loop as a non-invasive biomarker that selectively activates in alopecia areata, providing a precise target for JAK inhibitor treatments.

This study used machine learning models to analyze PCOS symptoms for early diagnosis, finding Support Vector Machine and VGG16 algorithms achieved high accuracy rates of 94.44% and 98.29% respectively.

This study found multiple factors, both inherited and acquired, that may lead to bradykinin-mediated angio-oedema, proposing a new classification based on bradykinin production and catabolism imbalance.

This study found that self-supervised pretraining significantly improves accuracy in medical image classifiers for dermatology and chest X-ray tasks, outperforming supervised baselines and showing robustness to distribution shifts with limited labeled data.

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 study reviews current methods for making and using platelet-rich plasma and fibrin, emphasizing the variability in clinical outcomes due to differences in preparation protocols, and calls for standardized guidelines and large-scale studies for better effectiveness in regenerative medicine.

This study used a probabilistic framework to show that platelet-rich plasma preparation results in significant variability in platelet dose due to factors like injected volume and concentration factor.

In this narrative review, the authors discuss regenerative substances like platelet-rich fibrin and mesenchymal stem cells in biological aesthetics, noting that while these methods show promise for regeneration, their safety, effectiveness, and durability remain uncertain due to limited and heterogeneous evidence.

This review discusses metal-organic frameworks for treating diabetic infected wounds and related applications, reporting no new clinical results but highlighting challenges like biosafety and production for future research.

This article provides guidelines for molecular genetic testing of congenital adrenal hyperplasia due to 21-hydroxylase deficiency, focusing on quality requirements, methodologies, and variant classification; it reports no new clinical results.

This study highlights the importance of creating customized, evidence-based hair care solutions by considering scalp types and environmental factors, confirming the effectiveness of multidisciplinary approaches integrating dermatology, cosmetology, and trichology to develop safe and efficient products and treatments.

This study observed that the relationships between various criteria used to classify systemic lupus erythematosus are more consistent with chance than predictable patterns, although connections within the same organ domain are relevant.

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 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 article examines differences in aging among ethnic populations and highlights cosmetic procedures specific to skin of color, but reports no new research findings.

In this study, metal-organic frameworks modified with stearic acid were used to deliver cardamonin to hair follicles, significantly promoting hair growth and cell proliferation in testosterone-challenged mice, suggesting potential benefits for androgenic alopecia treatment.

This study evaluated a novel, user-friendly approach for detecting hairfall trends over time using machine learning models. The Temporal Fusion Transformer model demonstrated high accuracy in identifying anomalies in hair shedding patterns, potentially aiding in the early detection of health risks related to hormonal fluctuations.

This study introduces a novel computational model using fuzzy logic and multi-criteria decision-making techniques to create a triage system for androgenetic alopecia management, stratifying patients into seven severity levels and aiding in resource allocation and treatment planning.

In this study, researchers observed a possible correlation between hair loss patterns and Mizaj (temperament) types, suggesting that hair loss patterns might serve as a diagnostic index for identifying individual temperaments according to the Unani system of medicine.

This review outlines evidence-based strategies for diagnosing pediatric hypopigmented disorders and emphasizes distinguishing vitiligo from self-limiting conditions through a systematic clinical approach; no new results are reported.

In this study, the researchers developed a deep learning framework to pre-emptively screen for adverse drug effects, showing strong predictive performance, including for increased bleeding risks with edoxaban compared to other anticoagulants.

In this case report, a 38-year-old woman with Parry–Romberg syndrome displayed left-sided facial atrophy and subclinical central nervous system involvement detectable by neuroimaging, suggesting that even symptom-free cases may benefit from systematic brain evaluations.

In this study, researchers characterized the clinical features of ophiasis, an uncommon type of alopecia areata, and proposed a new subtype classification that may help predict treatment response and guide management, noting that ophiasis generally has a chronic and refractory nature.

This review synthesizes evidence on strategies to preserve donor aesthetics and reserve in follicular unit extraction, emphasizing conservative extraction limits and long-term planning to prevent donor site morbidity.