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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.

This study found that cell-free RNA, particularly DNAJB9, shows potential as a biomarker for diagnosing and prognosing female androgenetic alopecia using a machine learning model.

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.

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 study reviews AI's role in aesthetic medicine, noting it enhances diagnostic accuracy and personalized treatment planning, but faces challenges like ethical concerns, algorithmic biases, and regulatory issues that need addressing for successful integration.

In this review, researchers reported that PCOS remains a complex condition with ongoing diagnostic and therapeutic challenges, highlighting recent innovations in diagnosis and treatment that provide alternative options for cases unresponsive to standard care.

This review highlights advancements in nanotechnology-based treatments for androgenetic alopecia, noting that these strategies could improve targeting and modulation of hair follicle environments compared to traditional therapies like minoxidil and finasteride, but also emphasizes challenges around safety, manufacturing, and regulation.

This review highlights the need for standardized reporting on fucoidan extract properties to better understand the relationships between chemical structures and bioactivities, and to improve the quality and utility of fucoidan-related data.

This review summarizes how single-cell omics technologies have advanced understanding of cellular regulatory programs in sheep and goats, but highlights limitations in genomic annotation and integration with population genetics for molecular breeding.

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.

In this study, the researchers performed a comparative analysis of drug-target interaction data from multiple databases to refine drug repurposing strategies, revealing potential associations between drug characteristics and therapeutic groups, and predicting repositioning opportunities for FDA-approved drugs across major cancer types.

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 review explores the skin benefits of exercise and discusses how artificial intelligence can tailor exercise programs to individual skin health needs, emphasizing the potential of AI-driven strategies in cosmetic dermatology for more personalized and adaptive skincare approaches.

This source does not report study results but describes the mission and peer review process of the Biomedical Journal of Scientific & Technical Research, emphasizing its focus on genetic, biomedical, and remedial research with technical knowledge integration.

This study identified risk of harm and set of competency and skills as key criteria in defining the profession of allied health in Malaysia, highlighting the need for integrated criteria in healthcare policy development.

In this study, researchers developed a method for high-resolution live imaging of leg regeneration in the crustacean Parhyale hawaiensis, which effectively captures the entire process at cellular resolution over 10 days while minimizing photodamage.

This article discusses drug repurposing as a strategy to find new uses for existing medications, highlighting its potential benefits like faster development and lower costs, while also addressing challenges such as drug specificity, ethical concerns, and regulatory issues.

This review aims to systematically evaluate the various types of antimicrobial wound dressings and current research on antimicrobial agents, providing insights for innovative treatments of infected wounds, due to the lack of comprehensive studies on their efficacy in promoting wound healing.

This review outlines the key principles and clinical applications of multimodal non-invasive skin imaging technologies, emphasizing their combined strengths in enhancing diagnosis and treatment assessment in dermatology.

This study reviews how individuals with diabetes experience accelerated skin aging and explores the implications for cosmetic treatments, highlighting the need for diabetes-informed dermatologic approaches due to limited evidence on safety and efficacy in this population.

In this study, a computational analysis of promoter regions in human fertility-related genes identified several new candidate regulatory motifs, but these require further experimental validation due to the limitations of being an in silico examination.

This review summarizes advancements in biomedical engineering for hair follicle regeneration, highlighting strategies like cell transplantation and tissue engineering to reconstruct hair follicles, and discusses both their technical limitations and potential future innovations in regenerative medicine.

This study reported that the PM-DBiGRU model enhances aspect-level sentiment classification in drug reviews, outperforming existing methods on the newly proposed SentiDrugs dataset.

This chapter reviews the challenges and future prospects of using nanotechnology and phytochemistry in developing safe, effective, and precision-based therapies for Polycystic Ovary Syndrome, without reporting new clinical findings.

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 evaluated various NLP models for detecting bias in medical curricula, finding that fine-tuned BERT models perform well, whereas LLMs, despite being state-of-the-art in many tasks, are unsuitable for this application.

This study reviews the transformative role of artificial intelligence in biomaterial design, highlighting its ability to reduce costs through virtual screening, enhance material performance, and predict biological interactions to advance personalized and precision medicine.

This review examines the reliance on formalized and automated protocols in fields like aviation and medicine, suggesting that such approaches may hinder the human capability of mètis needed to handle emergencies and dynamic ambiguities; it reports no new results.

This study introduced a novel, weakly supervised method for segmenting hair in Scanning Electron Microscope images using simple image-level annotations, achieving over 30% improvement in mean Hausdorff Distance compared to Unet and SAM, while enhancing interpretability and refinement.