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This perspective highlights how advancements in single-cell sequencing and digital pathology can help understand the complex mechanisms of immune responses, fibrosis, and tissue remodeling related to medical implants, aiming to address the challenges of implant-related tissue reactions reported in this study.

This study found that patients with alopecia areata had a significantly different gut microbiota composition compared to healthy controls, suggesting possible microbiota involvement in the disease's pathogenesis.

This article proposes a machine learning framework for classifying healthy hair and alopecia areata using image processing and classification techniques, but does not report new clinical findings.

This study identified four circulating microRNAs as highly predictive of frontal fibrosing alopecia status, suggesting potential roles in diagnostics and disease understanding.

This review examines physical methods like electron paramagnetic resonance spectroscopy, Raman spectroscopy, and differential scanning calorimetry, highlighting their complementary capabilities in analyzing biomolecular structures and mycobacterial interactions with reactive oxygen species and antioxidants.

This review emphasizes that collaboration between forensic anthropology and molecular anthropology could significantly improve the identification of unknown human remains by creating more comprehensive biological profiles.

MultiKano accurately identifies cell types in complex data better than existing methods.

This review found that current forensic DNA phenotyping panels for biogeographical ancestry and visible traits face significant limitations due to inconsistencies in terminology, genetic understanding, and genotyping technologies, highlighting the need for harmonization and further research.

This review discusses the role of cutaneous and intestinal microbiota in the development of alopecia areata, summarizing current literature without reporting new clinical results.

This review discusses the growing role of colorimetric sensors in food safety, highlighting their potential to enhance detection accuracy and manageability, while also noting challenges such as environmental interference and the need for further industrial validation.

This review highlights recent advances in ultrasound-based radiomics and radiogenomics for ovarian cancer, suggesting these techniques improve diagnostic accuracy and patient-specific treatment strategies, despite ongoing challenges with standardization and model interpretability.

This review highlights that gut dysbiosis and bacterial extracellular vesicles are key factors in PCOS pathophysiology, and suggests AI-driven analysis of these profiles could enhance diagnostic accuracy and treatment personalization, though ethical concerns like data privacy and bias must be considered.

This study found that ATR-FTIR spectroscopy combined with machine learning effectively differentiated alopecia areata patients from healthy controls with an AUC of 0.85, and also showed promise in predicting treatment response, particularly through alterations in the Amide I band.

This review consolidates various rational design strategies for nanozymes, emphasizing the mechanisms needed for precise design and exploring their applications in treating inflammatory diseases, diagnosing diseases, and environmental uses, while also discussing the challenges and future prospects in this emerging field.

This study introduces AlopeciaDet, a novel feature fusion technique, using camera images to detect Alopecia Areata with 99.45% accuracy, outperforming existing methods by leveraging CRSHOG and ResNet-50 features.

This study developed a two-step diagnostic model using transcriptome biomarkers from hair follicles to improve the accuracy of methamphetamine use disorder diagnosis, achieving high prediction accuracy in distinguishing non-recovered and almost-recovered patients from healthy controls.

This study developed a 3D bioprinted skin model to mimic pemphigus vulgaris, providing a tool to study disease mechanisms and test targeted therapies by reproducing the architecture and pathogenic disruptions of native skin.

In this study, researchers identified genes IRF2BP2 and EGFR as key to understanding double-coated fleece formation in Hetian sheep, offering insights that may advance machine learning-driven multi-omics selection models in sheep breeding.

Maintaining a balanced scalp microbiome can help reduce itchiness.

In this review, researchers introduced clinically tunable siRNA delivery systems for hair loss treatment, discussing design principles and analyzing relevant clinical trials to propose a framework for optimizing siRNA delivery in a clinical context.

In this study, a modified Xception deep learning model achieved a 92% accuracy rate in diagnosing hair and scalp disorders, significantly outperforming other models, suggesting AI could improve dermatological diagnostics' accuracy and accessibility.

This study found that a sub-fraction of Noni fruit, FEA-3, showed hair growth-promoting effects in a rabbit model of androgenic alopecia, similar to Minoxidil.

This review suggests that hyperspectral and terahertz imaging show promise in non-invasively assessing scalp changes associated with hair loss, but further validation is needed for clinical application.

This review highlights recent advances in personalized transdermal drug delivery systems, noting their potential for improved treatment efficacy and safety, but identifies significant challenges in clinical translation.

This review discusses therapeutic deep eutectic solvents as promising "green" solutions for enhancing drug solubility and delivery through the skin, reporting no new clinical results and highlighting future research directions.

This review highlights how nanotechnology enhances CRISPR-Cas9's potential for cancer treatment by improving delivery and stability, addressing key challenges like immunogenicity and delivery inefficiencies, and discusses recent advancements in stimuli-responsive nanoplatforms for precise genome editing.

This study found that a data-driven model using XGBoost effectively predicts individualized responses to minoxidil for androgenetic alopecia, outperforming traditional methods in accuracy and reliability.

This scoping review reports that while empirical evidence suggests an overlap between Long/Post Covid-19 syndrome, chronic fatigue syndrome, and fibromyalgia, the underlying molecular mechanisms remain unclear, highlighting the need for standardized definitions and rigorous methodologies in Long Covid research.

This review explores the mechanisms, current products, challenges, and innovative approaches related to cosmetics for hair loss prevention and growth promotion, emphasizing the need for multidisciplinary cooperation to enhance product development and market success.

This study demonstrated that Periplaneta americana extract significantly promoted hair regeneration in depilated mice by enhancing superoxide dismutase activity, upregulating vascular endothelial growth factor, modulating the FOXO/PI3K/AKT pathway, and restoring skin microbiome balance, suggesting its potential as a novel therapeutic candidate for alopecia.